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Sample records for forecast integration william

  1. July 2016 Systems Integration Solar Forecasting:

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    2016 Systems Integration Solar Forecasting: Maximizing its value for grid integration Introduction The forecasting of power generated by variable energy resources such as wind and solar has been the focus of academic and industrial research and development for as long as significant amounts of these renewable energy resources have been connected to the electric grid. The progress of forecasting capabilities has largely followed the penetration of the respective resources, with wind forecasting

  2. NREL: Transmission Grid Integration - Forecasting

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Forecasting NREL researchers use solar and wind resource assessment and forecasting techniques to develop models that better characterize the potential benefits and impacts of ...

  3. July 2016 Systems Integration Solar Forecasting:

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ... Those costs comprise fuel costs from expensive generators ... an improved-accuracy forecast of the solar power generation. ... analog ensemble for short-term probabilistic solar power ...

  4. Final Report - Integration of Behind-the-Meter PV Fleet Forecasts...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Final Report - Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System ...

  5. Weather forecast-based optimization of integrated energy systems.

    SciTech Connect

    Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.

    2009-03-01

    In this work, we establish an on-line optimization framework to exploit detailed weather forecast information in the operation of integrated energy systems, such as buildings and photovoltaic/wind hybrid systems. We first discuss how the use of traditional reactive operation strategies that neglect the future evolution of the ambient conditions can translate in high operating costs. To overcome this problem, we propose the use of a supervisory dynamic optimization strategy that can lead to more proactive and cost-effective operations. The strategy is based on the solution of a receding-horizon stochastic dynamic optimization problem. This permits the direct incorporation of economic objectives, statistical forecast information, and operational constraints. To obtain the weather forecast information, we employ a state-of-the-art forecasting model initialized with real meteorological data. The statistical ambient information is obtained from a set of realizations generated by the weather model executed in an operational setting. We present proof-of-concept simulation studies to demonstrate that the proposed framework can lead to significant savings (more than 18% reduction) in operating costs.

  6. Final Report - Integration of Behind-the-Meter PV Fleet Forecasts into

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Utility Grid System Operations | Department of Energy Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Final Report - Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Awardee: Clean Power Research Location: Napa, CA Subprogram: Systems Integration Funding Program: Solar Utility Networks: Replicable Innovations in Solar Energy (SUNRISE) Project: Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid

  7. Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Operations | Department of Energy Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Clean Power Research logo.jpg This project will address the need for a more accurate approach to forecasting net utility load by taking into consideration the contribution of customer-sited PV energy generation. Tasks within the project are designed to integrate novel PV power

  8. Integration of Behind-the-Meter PV Fleet Forecasts into Utility...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Forecasting behind-the-meter distributed PV generation power production within a region ... This project is expected to reduce the costs of integrating higher penetrations of PV into ...

  9. William Arndt

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    William Arndt William Arndt 11214167 10103524655099960 4159392778273133987 n William (Bill) Arndt Ph.D. Post Doc HPC optimization of Bioinformatics applications warndt@lbl.gov Berkeley Lab Berkeley, CA US William Arndt is a post doctoral software developer at NERSC. His focus is the targeted optimization of bioinformatics applications for use on HPC resources supported by NERSC. He is partially funded by the Joint Genome Institute and focuses on improving software heavily used by JGI

  10. William Tang

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    William Tang William Tang FES Requirements Worksheet 1.1. Project Information - Title Document Prepared By William Tang Project Title Title Principal Investigator William Tang Participating Organizations Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a brief description of your project - highlighting its computational aspect - and outline its scientific objectives for the next 3-5 years. Please list one or two

  11. William F. Hederman, Jr.

    Energy.gov [DOE]

    William F. Hederman is the Deputy Director for Systems Integration and Senior Advisor to the Secretary. Mr. Hederman is a trained electrical engineer and public policy analyst with decades of...

  12. William Johnston

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Johnston's long time research interests included high-speed, ... William E Johnston, "ESnet: Advanced Networking for ... System", Third International Conference on Broadband ...

  13. Ramping Effect on Forecast Use: Integrated Ramping as a Mitigation Strategy; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    Diakov, Victor; Barrows, Clayton; Brinkman, Gregory; Bloom, Aaron; Denholm, Paul

    2015-06-23

    Power generation ramping between forecasted (net) load set-points shift the generation (MWh) from its scheduled values. The Integrated Ramping is described as a method that mitigates this problem.

  14. Resource Information and Forecasting Group; Electricity, Resources, & Building Systems Integration (ERBSI) (Fact Sheet)

    SciTech Connect

    Not Available

    2009-11-01

    Researchers in the Resource Information and Forecasting group at NREL provide scientific, engineering, and analytical expertise to help characterize renewable energy resources and facilitate the integration of these clean energy sources into the electricity grid.

  15. Short-Term Load Forecasting Error Distributions and Implications for Renewable Integration Studies: Preprint

    SciTech Connect

    Hodge, B. M.; Lew, D.; Milligan, M.

    2013-01-01

    Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of the day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.

  16. Ben Williams

    Energy.gov [DOE]

    In October 2015, Ben Williams began serving as the interim senior communications specialist for the Office of Technology Transitions for the Department of Energy.Prior to his detail in the office,...

  17. Analysis and Synthesis of Load Forecasting Data for Renewable Integration Studies: Preprint

    SciTech Connect

    Steckler, N.; Florita, A.; Zhang, J.; Hodge, B. M.

    2013-11-01

    As renewable energy constitutes greater portions of the generation fleet, the importance of modeling uncertainty as part of integration studies also increases. In pursuit of optimal system operations, it is important to capture not only the definitive behavior of power plants, but also the risks associated with systemwide interactions. This research examines the dependence of load forecast errors on external predictor variables such as temperature, day type, and time of day. The analysis was utilized to create statistically relevant instances of sequential load forecasts with only a time series of historic, measured load available. The creation of such load forecasts relies on Bayesian techniques for informing and updating the model, thus providing a basis for networked and adaptive load forecast models in future operational applications.

  18. Williams named ASA Fellow

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Williams named ASA Fellow May 27, 2015 The American Statistical Association (ASA) has honored Brian Williams of LANL's Statistical Sciences group with the title of Fellow. Williams...

  19. Signature of William H. Goldstein Signature of William H. Goldstein

    National Nuclear Security Administration (NNSA)

    William H. Goldstein Signature of William H. Goldstein Signature of William H. Goldstein Signature of William H. Goldstein Signature of N. Nicole Nelson - Jean Signature of N. ...

  20. New Forecasting Tools Enhance Wind Energy Integration In Idaho and Oregon

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    New Forecasting Tools Enhance Wind Energy Integration in Idaho and Oregon Page 1 Under the American Recovery and Reinvestment Act of 2009, the U.S. Department of Energy and the electricity industry have jointly invested over $7.9 billion in 99 cost-shared Smart Grid Investment Grant projects to modernize the electric grid, strengthen cybersecurity, improve interoperability, and collect an unprecedented level of data on smart grid and customer operations. 1. Summary Idaho Power Company (IPC)

  1. Williams named ASA Fellow

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    May » Williams named ASA Fellow Williams named ASA Fellow The American Statistical Association (ASA) has honored Brian Williams with the title of Fellow. May 27, 2015 Brian Williams Brian Williams Communications Office (505) 667-7000 His research includes experimental design, computer experiments, Bayesian inference, spatial statistics, and statistical computing. The American Statistical Association (ASA) has honored Brian Williams of LANL's Statistical Sciences group with the title of Fellow.

  2. Unit commitment with wind power generation: integrating wind forecast uncertainty and stochastic programming.

    SciTech Connect

    Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M.

    2009-10-09

    We present a computational framework for integrating the state-of-the-art Weather Research and Forecasting (WRF) model in stochastic unit commitment/energy dispatch formulations that account for wind power uncertainty. We first enhance the WRF model with adjoint sensitivity analysis capabilities and a sampling technique implemented in a distributed-memory parallel computing architecture. We use these capabilities through an ensemble approach to model the uncertainty of the forecast errors. The wind power realizations are exploited through a closed-loop stochastic unit commitment/energy dispatch formulation. We discuss computational issues arising in the implementation of the framework. In addition, we validate the framework using real wind speed data obtained from a set of meteorological stations. We also build a simulated power system to demonstrate the developments.

  3. FY 1996 solid waste integrated life-cycle forecast characteristics summary. Volumes 1 and 2

    SciTech Connect

    Templeton, K.J.

    1996-05-23

    For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the physical waste forms, hazardous waste constituents, and radionuclides of the waste expected to be shipped to the CWC from 1996 through the remaining life cycle of the Hanford Site (assumed to extend to 2070). In previous years, forecast data has been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to two previous reports: the more detailed report on waste volumes, WHC-EP-0900, FY1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary and the report on expected containers, WHC-EP-0903, FY1996 Solid Waste Integrated Life-Cycle Forecast Container Summary. All three documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on two main characteristics: the physical waste forms and hazardous waste constituents of low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major generators for each waste category and waste characteristic are also discussed. The characteristics of low-level waste (LLW) are described in Appendix A. In addition, information on radionuclides present in the waste is provided in Appendix B. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste is expected to be received at the CWC over the remaining life cycle of the site. Based on

  4. Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model (Released in the STEO March 1998)

    Reports and Publications

    1998-01-01

    The blending of oxygenates, such as fuel ethanol and methyl tertiary butyl ether (MTBE), into motor gasoline has increased dramatically in the last few years because of the oxygenated and reformulated gasoline programs. Because of the significant role oxygenates now have in petroleum product markets, the Short-Term Integrated Forecasting System (STIFS) was revised to include supply and demand balances for fuel ethanol and MTBE. The STIFS model is used for producing forecasts in the Short-Term Energy Outlook. A review of the historical data sources and forecasting methodology for oxygenate production, imports, inventories, and demand is presented in this report.

  5. Tommy Williams | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Tommy Williams Jump to: navigation, search Name: Tommy Williams Place: Gainesville, FL Website: www.tommywilliams.com References: Tommy Williams1 Information About Partnership...

  6. NREL: Photovoltaics Research - William Nemeth

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Photo of William Nemeth William Nemeth Research Engineer On staff since: 2008 Phone number: 303-384-7801 Email William Nemeth Primary Research Interests Silicon solar cell...

  7. FY 1996 solid waste integrated life-cycle forecast container summary volume 1 and 2

    SciTech Connect

    Valero, O.J.

    1996-04-23

    For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the containers expected to be used for these waste shipments from 1996 through the remaining life cycle of the Hanford Site. In previous years, forecast data have been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to the more detailed report on waste volumes: WHC-EP0900, FY 1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary. Both of these documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on the types of containers that will be used for packaging low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major waste generators for each waste category and container type are also discussed. Containers used for low-level waste (LLW) are described in Appendix A, since LLW requires minimal treatment and storage prior to onsite disposal in the LLW burial grounds. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste are expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters.

  8. Wind Power Forecasting Data

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Operations Call 2012 Retrospective Reports 2012 Retrospective Reports 2011 Smart Grid Wind Integration Wind Integration Initiatives Wind Power Forecasting Wind Projects Email...

  9. Mr. William Steuteville

    Office of Legacy Management (LM)

    William Steuteville 3 HW 33 EPA Region III 841 Chestnut Street Philadelphia, Pennsylvania ... is well below the 100 pound reportable quantity (RQ) set by EPA for uranium nitrate. ...

  10. William Weaver | Department of Energy

    Energy.gov [DOE] (indexed site)

    William Weaver - Operational Readiness Authorization Basis William W. Weaver is a Nuclear Facilities and Tritium Risk Specialist in the Office of Chief Nuclear Safety, experienced ...

  11. William Brocker | Argonne National Laboratory

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    William Brocker ESH/QA Coordinator - EGS E-mail wbrocker

  12. Williams, Joel F Jr

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    ... that vou will be accompanying her at this meeting and to Put you on emails to Ms. ... Thanks Joel for both infG emails. From*. William, Joel F Jr rnvifto:Joel F Jr ...

  13. Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-09-01

    features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. In this report, a new methodology to predict the uncertainty ranges for the required balancing capacity, ramping capability and ramp duration is presented. Uncertainties created by system load forecast errors, wind and solar forecast errors, generation forced outages are taken into account. The uncertainty ranges are evaluated for different confidence levels of having the actual generation requirements within the corresponding limits. The methodology helps to identify system balancing reserve requirement based on a desired system performance levels, identify system “breaking points”, where the generation system becomes unable to follow the generation requirement curve with the user-specified probability level, and determine the time remaining to these potential events. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (California ISO) real life data have shown the effectiveness of the proposed approach. A tool developed based on the new methodology described in this report will be integrated with the California ISO systems. Contractual work is currently in place to integrate the tool with the AREVA EMS system.

  14. Integration of Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect

    Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Chakrabarti, Bhujanga B.; Subbarao, Krishnappa; Loutan, Clyde; Guttromson, Ross T.

    2010-04-20

    In this paper, a new approach to evaluate the uncertainty ranges for the required generation performance envelope, including the balancing capacity, ramping capability and ramp duration is presented. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (CAISO) real life data have shown the effectiveness and efficiency of the proposed approach.

  15. Roy Williams as recalled by Margaret Morrow ? Or: Roy Williams...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Margaret Morrow - Or: Roy Williams, a man with great presence and leadership (title as it appeared in The Oak Ridger) The series on Roy Williams has created a great response from...

  16. Solid waste integrated forecast technical (SWIFT) report: FY1997 to FY 2070, Revision 1

    SciTech Connect

    Valero, O.J.; Templeton, K.J.; Morgan, J.

    1997-01-07

    This web site provides an up-to-date report on the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the WM Project; program-level and waste class-specific estimates; background information on waste sources; and comparisons with previous forecasts and with other national data sources. This web site does not include: liquid waste (current or future generation); waste to be managed by the Environmental Restoration (EM-40) contractor (i.e., waste that will be disposed of at the Environmental Restoration Disposal Facility (ERDF)); or waste that has been received by the WM Project to date (i.e., inventory waste). The focus of this web site is on low-level mixed waste (LLMW), and transuranic waste (both non-mixed and mixed) (TRU(M)). Some details on low-level waste and hazardous waste are also provided. Currently, this web site is reporting data th at was requested on 10/14/96 and submitted on 10/25/96. The data represent a life cycle forecast covering all reported activities from FY97 through the end of each program's life cycle. Therefore, these data represent revisions from the previous FY97.0 Data Version, due primarily to revised estimates from PNNL. There is some useful information about the structure of this report in the SWIFT Report Web Site Overview.

  17. Solid Waste Integrated Forecast Technical (SWIFT) Report FY2001 to FY2046 Volume 1

    SciTech Connect

    BARCOT, R.A.

    2000-08-31

    This report provides up-to-date life cycle information about the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the WM Project; program-level and waste class-specific estimates; background information on waste sources; and comparisons to previous forecasts and other national data sources. This report does not include: waste to be managed by the Environmental Restoration (EM-40) contractor (i.e., waste that will be disposed of at the Environmental Restoration Disposal Facility (ERDF)); waste that has been received by the WM Project to date (i.e., inventory waste); mixed low-level waste that will be processed and disposed by the River Protection Program; and liquid waste (current or future generation). Although this report currently does not include liquid wastes, they may be added as information becomes available.

  18. William Alexander | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    William Alexander About Us William Alexander - Technical Programs and Outreach/Website Administrator William Alexander Mr. Alexander is a graduate of New Mexico Mining and Technology Institute, in Socorro New Mexico. He has been working in the Los Alamos area since 2007, where he started with Shaw Environmental Inc. During his time at Los Alamos National Laboratory Mr. Alexander worked in the Associate Directorate for Environmental Programs Division. In 2012 Mr. Alexander took a job with the

  19. William Perry | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    William Perry About Us William Perry - Former Secretary of Defense, Stanford University Professor Photo of William Perry William Perry is the Michael and Barbara Berberian Professor (emeritus) at Stanford University. He is a senior fellow at FSI and serves as co-director of the Nuclear Risk Reduction initiative and the Preventive Defense Project. He is an expert in U.S. foreign policy, national security and arms control. He was the co-director of CISAC from 1988 to 1993, during which time he was

  20. Bradley Williams | Department of Energy

    Energy.gov [DOE] (indexed site)

    Bradley Williams - Team Lead, Nuclear Energy University Programs Most Recent New Nuclear Energy Awards Give Students Hands-On Research Experience September 28...

  1. William Rock | Argonne National Laboratory

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    William R. Harvey About Us William R. Harvey, Ph.D. - President, Hampton University Dr. William R. Harvey Dr. William R. Harvey is President of Hampton University and 100% owner of the Pepsi Cola Bottling Company of Houghton, Michigan. Since 1978, he has served with distinction as President of Hampton University and created a monumental legacy during his thirty year tenure-one of the longest tenures of any sitting president of a college or university in the country. Dr. Harvey is described as

  2. William J. Clinton, 2000

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    1 Administration of William J. Clinton, 2000 / Apr. 22 have the vehicles they want with the effi- ciency they deserve. More than 100 years ago, the great Amer- ican poet Henry Wadsworth Longfellow re- minded us that ''nature is a revelation of God.'' This Earth Day, let us remember that we are only stewards, in our time, of the Earth God gave us for all time. And let us strengthen our resolve to preserve the beauty and the natural bounty that sustains us and must sustain generations yet to come.

  3. Trish Williams | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Trish Williams About Us Trish Williams - Communications Specialist, EERE Communications Office Most Recent Friedman Sets Sights on Accelerating America's Transition to a Clean Energy Economy July 22 Friedman Sets Sights on Accelerating America's Transition to a Clean Energy Economy July 12 National Clean Energy Incubators Spawn New Commercialization Centers June 27

  4. Williams Energy Services | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Energy Services Jump to: navigation, search Name: Williams Energy Services Place: Tulsa, OK Website: www.williamsenergyservices.com References: Williams Energy Services1...

  5. Williams Stone Wind Turbine | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Stone Wind Turbine Jump to: navigation, search Name Williams Stone Wind Turbine Facility Williams Stone Wind Turbine Sector Wind energy Facility Type Community Wind Facility Status...

  6. 2016 Solar Forecasting Workshop | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Solar Forecasting Workshop 2016 Solar Forecasting Workshop On August 3, 2016, the SunShot Initiative's systems integration subprogram hosted the Solar Forecasting Workshop to convene experts in the areas of bulk power system operations, distribution system operations, weather and solar irradiance forecasting, and photovoltaic system operation and modeling. The goal was to identify the technical challenges and opportunities in solar forecasting as a capability that can significantly reduce the

  7. Federal Energy and Water Management Award Winners William Kuster...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    William Kuster, John McDuffie, Dennis Svalstad, William Turnbull and Steven White Federal Energy and Water Management Award Winners William Kuster, John McDuffie, Dennis Svalstad, ...

  8. Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-01-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter

  9. William E. Murphie | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    William E. Murphie About Us William E. Murphie - Manager of Portsmouth/Paducah Project Office William E. Murphie William Murphie was appointed in 2003 to manage the activities of the U.S. Department of Energy's newly created Portsmouth/Paducah Project Office (PPPO) in Lexington, Kentucky to provide leadership and focus to the specific cleanup challenges at the Portsmouth and Paducah Gaseous Diffusion Plants. Bill's management and oversight responsibilities encompass environmental remediation,

  10. Melvin G. Williams, Jr. | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Melvin G. Williams, Jr. About Us Melvin G. Williams, Jr. - Former Associate Deputy Secretary Melvin G. Williams, Jr. Melvin G. Williams Jr., Vice Admiral, U.S. Navy (retired), served as the Associate Deputy Secretary of Energy until February 2013. As a Presidential Appointee at the U.S. Department of Energy, he served as the key leader responsible for the Department's management and operational excellence. He reported directly to the Secretary of Energy and the Deputy Secretary, and drove

  11. William N. Haberichter | Argonne National Laboratory

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    William N. Haberichter Argonne Associate Telephone (630) 252-7525 E-mail wnh@hep.anl

  12. Value of Wind Power Forecasting

    SciTech Connect

    Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

    2011-04-01

    This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

  13. SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2005 THRU FY2035 2005.0 VOLUME 2

    SciTech Connect

    BARCOT, R.A.

    2005-08-17

    This report provides up-to-date life cycle information about the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: (1) an overview of Hanford-wide solid waste to be managed by the WM Project; (2) multi-level and waste class-specific estimates; (3) background information on waste sources; and (4) comparisons to previous forecasts and other national data sources. The focus of this report is low-level waste (LLW), mixed low-level waste (MLLW), and transuranic waste, both non-mixed and mixed (TRU(M)). Some details on hazardous waste are also provided, however, this information is not considered comprehensive. This report includes data requested in December, 2004 with updates through March 31,2005. The data represent a life cycle forecast covering all reported activities from FY2005 through the end of each program's life cycle and are an update of the previous FY2004.1 data version.

  14. Solar Forecasting

    Energy.gov [DOE]

    On December 7, 2012, DOE announced $8 million to fund two solar projects that are helping utilities and grid operators better forecast when, where, and how much solar power will be produced at U.S....

  15. Funding Opportunity Announcement: Solar Forecasting 2 | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy Solar Forecasting 2 Funding Opportunity Announcement: Solar Forecasting 2 Subprogram: Systems Integration Funding Number: DE-FOA-0001649 Funding Amount: $10 million Description The Solar Forecasting 2 funding program will support projects that enable grid operators to better forecast how much solar energy will be added to the grid and accelerate the integration of these forecasts into energy management systems used by grid operators and utility companies. These tools will enable grid

  16. William A. Goddard III - JCAP

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    william a. goddard iii Principal Investigator Email: wag@wag.caltech.edu Dr. Goddard is a pioneer in developing methods for quantum mechanics (QM), force fields, molecular dynamics (MD), and Monte Carlo predictions on chemical and materials systems and is actively involved in applying these methods to ceramics, semiconductors, superconductors, thermoelectrics, metal alloys, polymers, proteins, nuclei acids, Pharma ligands, nanotechnology, and energetic materials. He uses QM methods to determine

  17. SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2003 THRU FY2046 VERSION 2003.1 VOLUME 2 [SEC 1 & 2

    SciTech Connect

    BARCOT, R.A.

    2003-12-01

    This report includes data requested on September 10, 2002 and includes radioactive solid waste forecasting updates through December 31, 2002. The FY2003.0 request is the primary forecast for fiscal year FY 2003.

  18. William Fowler and Elements in the Stars

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    William Fowler and Elements in the Stars Resources with Additional Information William A. Fowler Courtesy AIP Emilio Segrè Visual Archives 'William A. Fowler ... shared the 1983 Nobel Prize in physics for his research into the creation of chemical elements inside stars ... . During his career in nuclear physics and nuclear astrophysics, which spanned more that 60 years, Fowler was primarily concerned with studies of fusion reactions--how the nuclei of lighter chemical elements fuse to create

  19. Williams, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Williams, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.2494566, -112.1910031 Show Map Loading map... "minzoom":false,"mappingser...

  20. Williams Biomass Facility | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    USA Biomass National Map Retrieved from "http:en.openei.orgwindex.php?titleWilliamsBiomassFacility&oldid398342" Feedback Contact needs updating Image needs updating...

  1. Kumar, Jitendra; Hoffman, Forrest; Hargrove, William; Mills,...

    Office of Scientific and Technical Information (OSTI)

    based Sampling Network Design for the State of Alaska Kumar, Jitendra; Hoffman, Forrest; Hargrove, William; Mills, Richard 54 Environmental Sciences Ecoregions; Representativeness;...

  2. William R. Harvey | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    William R. Harvey About Us William R. Harvey, Ph.D. - President, Hampton University Dr. William R. Harvey Dr. William R. Harvey is President of Hampton University and 100% owner of the Pepsi Cola Bottling Company of Houghton, Michigan. Since 1978, he has served with distinction as President of Hampton University and created a monumental legacy during his thirty year tenure-one of the longest tenures of any sitting president of a college or university in the country. Dr. Harvey is described as

  3. William Scullin | Argonne Leadership Computing Facility

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    William Scullin Assistant Computational Scientist Argonne National Laboratory 9700 South Cass Avenue Building 240 - Rm. 3122 Argonne, IL 60439 630-252-6412 wscullin@alcf.anl

  4. Forecast Change

    Annual Energy Outlook

    Forecast Change 2011 2012 2013 2014 2015 2016 from 2015 United States Usage (kWh) 3,444 3,354 3,129 3,037 3,151 3,302 4.8% Price (centskWh) 12.06 12.09 12.58 13.04 12.95 12.84 ...

  5. Hawaii Energy Strategy: Program guide. [Contains special sections on analytical energy forecasting, renewable energy resource assessment, demand-side energy management, energy vulnerability assessment, and energy strategy integration

    SciTech Connect

    Not Available

    1992-09-01

    The Hawaii Energy Strategy program, or HES, is a set of seven projects which will produce an integrated energy strategy for the State of Hawaii. It will include a comprehensive energy vulnerability assessment with recommended courses of action to decrease Hawaii's energy vulnerability and to better prepare for an effective response to any energy emergency or supply disruption. The seven projects are designed to increase understanding of Hawaii's energy situation and to produce recommendations to achieve the State energy objectives of: Dependable, efficient, and economical state-wide energy systems capable of supporting the needs of the people, and increased energy self-sufficiency. The seven projects under the Hawaii Energy Strategy program include: Project 1: Develop Analytical Energy Forecasting Model for the State of Hawaii. Project 2: Fossil Energy Review and Analysis. Project 3: Renewable Energy Resource Assessment and Development Program. Project 4: Demand-Side Management Program. Project 5: Transportation Energy Strategy. Project 6: Energy Vulnerability Assessment Report and Contingency Planning. Project 7: Energy Strategy Integration and Evaluation System.

  6. William E. and Diane M. Spicer Young Investigator Award | Stanford...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    William E. and Diane M. Spicer Young Investigator Award William E. and Diane M. Spicer Young Investigator Award William E. Spicer (1929-2004) was an esteemed member of the...

  7. DOE - Office of Legacy Management -- Baker and Williams Co -...

    Office of Legacy Management (LM)

    Baker and Williams Co - NJ 13 FUSRAP Considered Sites Site: Baker and Williams Co (NJ 13) Eliminated from consideration under FUSRAP Designated Name: Not Designated Alternate Name:...

  8. Mountrail-Williams Elec Coop | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Mountrail-Williams Elec Coop Jump to: navigation, search Name: Mountrail-Williams Elec Coop Place: North Dakota Phone Number: Williston Office- 701-577-3765 -- Stanley Office-...

  9. City of Williams - AZ, Arizona (Utility Company) | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    Williams - AZ, Arizona (Utility Company) Jump to: navigation, search Name: City of Williams - AZ Place: Arizona Phone Number: 928-635-2667 or 928-635-4451 Website:...

  10. W&M, JLab Host International Neutrino Workshop (William & Mary...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    W&M, JLab Host International Neutrino Workshop (William & Mary News & Events) External Link: http:www.wm.edunewsstories2012william--mary-hosts-international-neutrino-w... By ...

  11. William S. Maharay: Before the Subcommittee on Government Management...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Testimony of William S. Maharay, Deputy Inspector General for Audit Services U.S. ... TESTIMONY OF WILLIAM S. MAHARAY DEPUTY INSPECTOR GENERAL FOR AUDIT SERVICES U.S. ...

  12. Sherwin-Williams' Richmond, Kentucky, Facility Achieves 26% Energy...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Sherwin-Williams' Richmond, Kentucky, Facility Achieves 26% Energy Intensity Reduction; Leads to Corporate Adoption of Save Energy Now LEADER Sherwin-Williams' Richmond, Kentucky, ...

  13. EA-158 Williams Energy Services Company | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    8 Williams Energy Services Company EA-158 Williams Energy Services Company Order authorizing Williams Energy Services Company to export electric energy to Canada. EA-158 Williams Energy Services Company (45.04 KB) More Documents & Publications EA-162 PP&L, Inc EA-164 Constellation Power Source

  14. William Bryan, OE-30 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    William Bryan, OE-30 About Us William Bryan, OE-30 - Deputy Assistant Secretary, Infrastructure Security & Energy Restoration Mr. Bryan is the Deputy Assistant Secretary for Infrastructure Security and Energy Restoration in the U.S. Department of Energy's (DOE) Office of Electricity Delivery and Energy Reliability (OE). The office of Infrastructure Security and Energy Restoration (ISER) works with the National Security Staff, other U.S. government agencies, and international partners to

  15. Federal Energy and Water Management Award Winners William Kuster, John

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    McDuffie, Dennis Svalstad, William Turnbull and Steven White | Department of Energy William Kuster, John McDuffie, Dennis Svalstad, William Turnbull and Steven White Federal Energy and Water Management Award Winners William Kuster, John McDuffie, Dennis Svalstad, William Turnbull and Steven White fewm13_acclangley_highres.pdf (3.11 MB) fewm13_acclangley.pdf (2.8 MB) More Documents & Publications Table 4 - DOE Technical Standards Requiring Central Technical Authority (CTA) Concurrence

  16. Today's Forecast: Improved Wind Predictions | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical

  17. Anderson-Cook wins William G. Hunter Award

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Anderson-Cook Wins William G. Hunter Award Anderson-Cook wins William G. Hunter Award The award is named and presented annually in honor of the Statistics Division's founding chair, William G. Hunter. November 6, 2012 Christine Anderson-Cook Christine Anderson-Cook Christine Anderson-Cook of LANL's Statistical Sciences group has received the 2012 William G. Hunter Award from the American Society for Quality-Statistics Division. The award is named and presented annually in honor of the Statistics

  18. William & Mary Undergrad Receives JSA Research Assistantship | Jefferson

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Lab William & Mary Undergrad Receives JSA Research Assistantship William & Mary Undergrad Receives JSA Research Assistantship Alice Perrin, a senior physics major at The College of William and Mary Alice Perrin, a senior physics major at The College of William and Mary is the recipient of the 2014-15 Jefferson Science Associates Minority/Female Undergraduate Research Assistantship (JSA MFURA) at Jefferson Lab. Her assistantship project involves setting up a testing facility to

  19. Builders Challenge High Performance Builder Spotlight Tommy Williams Homes

    SciTech Connect

    2010-02-05

    Builders Challenge fact sheet highlighting performance and energy-efficiency features of Tommy Williams Homes, Longleaf case study, Gainesville, FL

  20. Geothermal Literature Review At General Us Region (Williams ...

    OpenEI (Open Energy Information) [EERE & EIA]

    navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermal Literature Review At General Us Region (Williams & Reed, 2005) Exploration Activity Details...

  1. Roy Williams as recalled by his son and family ? Or: Roy Williams...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    his son and family - Or: Roy Williams: A leader among many (title at it appeared The Oak Ridger) The rewards for writing stories about Y-12 history come in many and varied formsl...

  2. Solid waste integrated forecast technical (SWEFT) report: FY1997 to FY 2070 - Document number changed to HNF-0918 at revision 1 - 1/7/97

    SciTech Connect

    Valero, O.J.

    1996-10-03

    This web site provides an up-to-date report on the radioactive solid waste expected to be managed at Hanford`s Solid Waste (SW) Program from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the SW Program; program- level and waste class-specific estimates; background information on waste sources; and Li comparisons with previous forecasts and with other national data sources. The focus of this web site is on low- level mixed waste (LLMW), and transuranic waste (both non-mixed and mixed) (TRU(M)). Some details on low-level waste and hazardous waste are also provided. Currently, this site is reporting data current as of 9/96. The data represent a life cycle forecast covering all reported activities from FY97 through the end of each program`s life cycle.

  3. Forecastability as a Design Criterion in Wind Resource Assessment: Preprint

    SciTech Connect

    Zhang, J.; Hodge, B. M.

    2014-04-01

    This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

  4. John J. MacWilliams | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    J. MacWilliams About Us John J. MacWilliams - Associate Deputy Secretary John J. MacWilliams John J. MacWilliams was appointed in August 2015 as Associate Deputy Secretary of the U.S. Department of Energy. He also serves as the Department's Chief Risk Officer and advances Secretarial priorities of enterprise-wide approaches to innovative finance, risk management, project management, nuclear and cyber security. Mr. MacWilliams joined the Department in May 2013 as a Senior Advisor to the

  5. Notice of Intent to Issue Solar Forecasting 2 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Solar Forecasting 2 Notice of Intent to Issue Solar Forecasting 2 Subprogram: Systems Integration Funding Number: DE-FOA-0001658 Funding Amount: $10,000,000 The SunShot Initiative intends to release a funding opportunity announcement (FOA) to support advancements in solar forecasting to enable higher penetration of solar power in the electric grid. The Solar Forecasting 2 FOA will focus on improving solar forecasting skills, especially during challenging conditions, such as partly cloudy weather

  6. William M. Gausman Vice President - Asset Management

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    01Ninth Street, NW Washington, DC 20068 202-872-3227 William M. Gausman Vice President - Asset Management February 9, 2007 Lawrence Mansueti Office of Electricity Delivery and Energy Reliability US Department of Energy Rm. 8H-033 1000 Independence Avenue Washington, D. C. 20585 Re: Potomac River Generating Station Department of Energy, Case No. EO-05-01 Dear Mr. Mansueti: Potomac Electric Power Company ("Pepco") is providing you with the following information regarding the revised plan

  7. Bicycle Generator Lightbar Indicator ----- Inventors William Evans

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    (Princeton University), Andrew Zwicker, and Shana Weber (Princeton University) | Princeton Plasma Physics Lab Bicycle Generator Lightbar Indicator ----- Inventors William Evans (Princeton University), Andrew Zwicker, and Shana Weber (Princeton University) This invention is a series of incandescent light bulbs that progressively brighten in response to a bicycler's physical effort. By monitoring the number of bulbs illuminated in a "light tower," the bicycler is able to judge the

  8. probabilistic energy production forecasts

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    energy production forecasts - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary ...

  9. Solar Forecasting Technical Workshop

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Forecasting Technical Workshop August 3, 2016 901 D St SW, Suite #930, Washington, DC Agenda 8:00-8:30 Check-in 8:30-8:45 Welcome & Opening remarks Guohui Yuan, DOE 8:45-9:15 Overview of Motivation and Techniques for Solar Forecasting Jan Kleissl, UCSD 9:15-9:45 Collaborative Research on Solar Power Forecasting: Challenges, Methods, and Assessment Tara Jensen, NCAR 9:45-10:00 Break 10:00-10:30 Machine-learning Based Enhancements for Renewable Energy Forecasting: From Research to Applications

  10. Wind Power Forecasting

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    data Presentations BPA Super Forecast Methodology Related Links Near Real-time Wind Animation Meteorological Data Customer Supplied Generation Imbalance Dynamic Transfer Limits...

  11. Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting: Preprint

    SciTech Connect

    Zhang, J.; Florita, A.; Hodge, B. M.; Freedman, J.

    2014-05-01

    The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.

  12. Sherwin-Williams' Richmond, Kentucky, Facility Achieves 26% Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Intensity Reduction; Leads to Corporate Adoption of Save Energy Now LEADER | Department of Energy Sherwin-Williams' Richmond, Kentucky, Facility Achieves 26% Energy Intensity Reduction; Leads to Corporate Adoption of Save Energy Now LEADER Sherwin-Williams' Richmond, Kentucky, Facility Achieves 26% Energy Intensity Reduction; Leads to Corporate Adoption of Save Energy Now LEADER This case study summarizes energy efficiency achievements made by Sherwin-Williams' Richmond, Kentucky,

  13. William E. and Diane M. Spicer Young Investigator Award | Stanford

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Synchrotron Radiation Lightsource William E. and Diane M. Spicer Young Investigator Award William E. and Diane M. Spicer Young Investigator Award William E. Spicer (1929-2004) was an esteemed member of the international scientific community as a teacher and researcher in electrical engineering, applied physics and materials science. Bill spent 40 years as a professor at Stanford where he pioneered the technique of ultraviolet photoemission spectroscopy and its subsequent expansion into the

  14. Anderson-Cook wins William G. Hunter Award

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Anderson-Cook wins William G. Hunter Award November 6, 2012 Christine Anderson-Cook of LANL's Statistical Sciences group has received the 2012 William G. Hunter Award from the American Society for Quality-Statistics Division. The award is named and presented annually in honor of the Statistics Division's founding chair, William G. Hunter. The award is presented to a person whose qualities mirror those of Hunter. These include substantial contributions to statistical consulting, education for

  15. Dianne Williams Wilburn-Creating her own destiny

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Dianne Williams Wilburn Dianne Williams Wilburn-Creating her own destiny Having monitored environmental compliance for New Mexico State and analyzed water chemistry for a nuclear power plant in Virginia, Wilburn is well versed in environmental health and radiation safety. March 11, 2014 Dianne Williams Wilburn Having monitored environmental compliance for New Mexico State and analyzed water chemistry for a nuclear power plant in Virginia, Wilburn is well versed in environmental health and

  16. Buildng America Whole-House Solutions for New Homes: William...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    More Documents & Publications Building America Whole-House Solutions for New Homes: Tommy Williams Homes, Gainesville, Florida Building America Best Practices Series Volume 15: 40% ...

  17. Static Temperature Survey At San Andreas Region (Williams, Et...

    OpenEI (Open Energy Information) [EERE & EIA]

    San Andreas Region (Williams, Et Al., 2004) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Static Temperature Survey At San Andreas Region...

  18. Geographic Information System At U.S. West Region (Williams ...

    OpenEI (Open Energy Information) [EERE & EIA]

    U.S. West Region (Williams & Deangelo, 2008) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geographic Information System At U.S. West Region...

  19. MHK Projects/Williams Point Project | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Williams Point Project < MHK Projects Jump to: navigation, search << Return to the MHK database homepage Loading map... "minzoom":false,"mappingservice":"googlemaps3","type":"ROAD...

  20. Anderson-Cook wins William G. Hunter Award

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Christine Anderson-Cook Christine Anderson-Cook Christine Anderson-Cook of LANL's Statistical Sciences group has received the 2012 William G. Hunter Award from the American...

  1. Buildng America Whole-House Solutions for New Homes: William...

    Energy.gov [DOE] (indexed site)

    - Tampa, Florida (691.72 KB) More Documents & Publications Building America Whole-House Solutions for New Homes: Tommy Williams Homes, Gainesville, Florida Building America ...

  2. Albert "Al" J. Williams | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Albert "Al" J. Williams About Us Albert "Al" J. Williams - President, Chevron Pipe Line Company (CPL) Albert “Al” J. Williams Albert (Al) J. Williams is president of Chevron Pipe Line Company (CPL), a wholly-owned subsidiary of Chevron Corporation, a role he assumed in May 2014. He is responsible for managing an extensive network of crude oil, natural gas and refined product pipelines, as well as storage facilities in North America. CPL also provides technical,

  3. Replace Fossil Fuels, Final Technical Report Roberts, William...

    Office of Scientific and Technical Information (OSTI)

    Crude Glycerol as Cost-Effective Fuel for Combined Heat and Power to Replace Fossil Fuels, Final Technical Report Roberts, William L 09 BIOMASS FUELS biofuels, glycerin, glycerol,...

  4. Williams To Head Livermore Site Office | National Nuclear Security...

    National Nuclear Security Administration (NNSA)

    Williams To Head Livermore Site Office August 14, 2008 WASHINGTON, D.C. - Alice C. ... and environment, has been named the new Livermore Site Office manager, effective November ...

  5. Barnes, Cris William [Los Alamos National Laboratory]; Kippen...

    Office of Scientific and Technical Information (OSTI)

    MaRIE: A facility for time-dependent materials science at the mesoscale Barnes, Cris William Los Alamos National Laboratory; Kippen, Karen Elizabeth Los Alamos National...

  6. Challenge of Dynamic Mesoscale Imaging Barnes, Cris William ...

    Office of Scientific and Technical Information (OSTI)

    The Matter-Radiation Interactions in Extremes Project, and the Challenge of Dynamic Mesoscale Imaging Barnes, Cris William Los Alamos National Laboratory; Barber, John L. Los...

  7. Two NNSA Awards for LSO's Alice Williams | National Nuclear Security...

    National Nuclear Security Administration (NNSA)

    NNSA Blog Livermore Site Office Manager Alice Williams yesterday received the NNSA Gold Medal for distinguished service in the national security of the United States and the...

  8. Microsoft PowerPoint - Briefings_Williams [Compatibility Mode...

    Office of Environmental Management (EM)

    Jeff Williams Project Director National Transportation Stakeholders Forum Bloomington, Minnesota May 13-15, 2014 NFST Established to Plan for Interim Storage and Transportation ...

  9. William Herschel, the First Observational Cosmologist

    ScienceCinema

    Lemonick, Michael [Princeton University and Time Magazine, Princeton, New Jersey, United States

    2016-07-12

    In the late 1700s, a composer, orchestra director and soloist named William Herschel became fascinated with astronomy, and, having built his own reflecting telescope, went out in his garden in Bath, England, one night and discovered Uranus—the first planet in human history ever found by an individual. The feat earned him a lifetime pension from King George III. But Herschel considered the discovery to be relatively unimportant in comparison to his real work: understanding the composition, structure and evolution of the universe. In pursuing that work, he became the first observational cosmologist.

  10. Data Acquisition-Manipulation At U.S. West Region (Williams ...

    OpenEI (Open Energy Information) [EERE & EIA]

    Williams & Deangelo, 2008) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Data Acquisition-Manipulation At U.S. West Region (Williams &...

  11. Signature of George Miller Signature of George Miller Signature of Alice Williams

    National Nuclear Security Administration (NNSA)

    George Miller Signature of George Miller Signature of Alice Williams Signature of Alice Williams Signature of Homer Williamson Signature of Homer Williamson Signature of Homer Williamson

  12. Camp William Utah National Guard Wind Farm II | Open Energy Informatio...

    OpenEI (Open Energy Information) [EERE & EIA]

    II Jump to: navigation, search Name Camp William Utah National Guard Wind Farm II Facility Camp William Utah National Guard Sector Wind energy Facility Type Community Wind Facility...

  13. 2016 SSL Forecast Report

    Energy.gov [DOE]

    The DOE report, Energy Savings Forecast of Solid-State Lighting in General Illumination Applications, is a biannual report which models the adoption of LEDs in the U.S. general-lighting market,...

  14. SSL Forecast Report

    Energy.gov [DOE]

    The DOE report, Energy Savings Forecast of Solid-State Lighting in General Illumination Applications, is the latest edition of a biannual report which models the adoption of LEDs in the U.S....

  15. Acquisition Forecast | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Acquisition Forecast Acquisition Forecast Acquisition Forecast It is the policy of the U.S. Department of Energy (DOE) to provide timely information to the public regarding DOE's forecast of future prime contracting opportunities and subcontracting opportunities which are available via the Department's major site and facilities management contractors. This forecast has been expanded to also provide timely status information for ongoing prime contracting actions that are valued in excess of the

  16. Operational forecasting based on a modified Weather Research and Forecasting model

    SciTech Connect

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

    Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

  17. King William County, Virginia: Energy Resources | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. King William County is a county in Virginia. Its FIPS County Code is 101. It is classified...

  18. Roy Williams as recalled by Bill Wilcox and others

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    worked for Roy, calling him a "wonderful boss that everyone liked." I also asked Ken Brady to comment on Roy Williams. I believe his insight is helpful to demonstrate a...

  19. From: Miller, William [mailto:wmiller@McCarter.com

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ... If you have any questions regarding this email or our questions, please contact me or Rick Murphy at AGA. Thank you - Bud William T. Miller | Partner McCARTER & ENGLISH, LLP 1015 ...

  20. From: Miller, William [mailto:wmiller@McCarter.com

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ... Bud William T. Miller | Partner McCARTER & ENGLISH, LLP 1015 15th Street, NW, 12th Floor | ... message from the law firm of McCarter & English, LLP is for the sole use of the intended ...

  1. From: Miller, William [mailto:wmiller@McCarter.com

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ... whether DOE intends to heed this request. Bud William T. Miller | Partner McCARTER & ENGLISH, LLP 1015 15th Street, NW, 12th Floor | Washington DC, 20005 T: 202-753-3420 F: ...

  2. TO: Alexander Williams FROM: Ed MitchelfiM

    Office of Legacy Management (LM)

    420 OTS NOTE . DATE: September 13, 1990 TO: Alexander Williams FROM: Ed MitchelfiM NY 463 fusrap7 SUBJECT: Elimination Recommendation for American Machine and Foundry in Buffalo...

  3. Williams County, Ohio: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. Williams County is a county in Ohio. Its FIPS County Code is 171. It is classified as ASHRAE...

  4. Williams Creek, Indiana: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. Williams Creek is a town in Marion County, Indiana. It falls under Indiana's 5th congressional...

  5. Williams County, North Dakota: Energy Resources | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. Williams County is a county in North Dakota. Its FIPS County Code is 105. It is classified as...

  6. Y-12s Moon Rocks and Jim Williams

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Moon Rocks and Jim Williams Often I am stopped and given suggestions about what would be good information to include in the history of Y-12 being published weekly in The Oak...

  7. The Honorable Robert E. Williams 44 W. Washington Street

    Office of Legacy Management (LM)

    If you have any questions, please feel free to call me at 301-427-1721 or Dr. W. Alexander Williams (301-427-1719) oi my staff. Sincerely, 7 4 I T- 2L ( &.&&& LAJ- ...

  8. Dr. Ellen Williams Confirmed as Director of ARPA-E

    Energy.gov [DOE]

    WASHINGTON – Dr. Ellen Williams was confirmed by the United States Senate on Monday, December 8, 2014 as the Director of the Department of Energy’s Advanced Research Projects Agency – Energy (ARPA-E).

  9. VBH-0079- In the Matter of William Cor

    Energy.gov [DOE]

    This Decision involves a whistleblower complaint filed by William Cor under the Department of Energy's (DOE) Contractor Employee Protection Program. From August 1998 to September 2001, Mr. Cor was...

  10. TBU-0045- In the Matter of William Cor

    Energy.gov [DOE]

    William Cor (the complainant or the employee), appeals the dismissal of his complaint of retaliation filed under 10 C.F.R. Part 708, the Department of Energy (DOE) Contractor Employee Protection...

  11. John William (Bill) Ebert Jr. ? Longtime Y-12 Maintenance Manager

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    John William (Bill) Ebert Jr. - Longtime Y-12 Maintenance Manager I knew him as "Mr. Ebert" when his office was in Building 9734. I used to park my bicycle in the hallway just...

  12. The Wind Forecast Improvement Project (WFIP). A Public-Private Partnership Addressing Wind Energy Forecast Needs

    SciTech Connect

    Wilczak, James M.; Finley, Cathy; Freedman, Jeff; Cline, Joel; Bianco, L.; Olson, J.; Djalaova, I.; Sheridan, L.; Ahlstrom, M.; Manobianco, J.; Zack, J.; Carley, J.; Benjamin, S.; Coulter, R. L.; Berg, Larry K.; Mirocha, Jeff D.; Clawson, K.; Natenberg, E.; Marquis, M.

    2015-10-30

    The Wind Forecast Improvement Project (WFIP) is a public-private research program, the goals of which are to improve the accuracy of short-term (0-6 hr) wind power forecasts for the wind energy industry and then to quantify the economic savings that accrue from more efficient integration of wind energy into the electrical grid. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that include the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models to improve model initial conditions; and second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the U.S. (the upper Great Plains, and Texas), and included 12 wind profiling radars, 12 sodars, 184 instrumented tall towers and over 400 nacelle anemometers (provided by private industry), lidar, and several surface flux stations. Results demonstrate that a substantial improvement of up to 14% relative reduction in power root mean square error (RMSE) was achieved from the combination of improved NOAA numerical weather prediction (NWP) models and assimilation of the new observations. Data denial experiments run over select periods of time demonstrate that up to a 6% relative improvement came from the new observations. The use of ensemble forecasts produced even larger forecast improvements. Based on the success of WFIP, DOE is planning follow-on field programs.

  13. William S. Maharay: Before the Subcommittee on Government Management,

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Organization and Procurement Committee on Oversight and Government Reform U.S. House | Department of Energy William S. Maharay: Before the Subcommittee on Government Management, Organization and Procurement Committee on Oversight and Government Reform U.S. House William S. Maharay: Before the Subcommittee on Government Management, Organization and Procurement Committee on Oversight and Government Reform U.S. House March 20, 2007 Before the Subcommittee on Government Management, Organization

  14. William Fowler and Elements in the Stars

    Office of Scientific and Technical Information (OSTI)

    ... Integrated Flux Distributions in Neutron Capture in Stars, DOE Technical Report, September 23, 1965 Helium (3) Rich Solar Flares, DOE Technical Report, May 3, 1977 Top Additional ...

  15. QER- Comment of William Smith III

    Energy.gov [DOE]

    ://www.rmi.org/Knowledge-Center/Library/E05-14_NuclearPowerEconomics.... If you have not yet done so, I strongly urge you to contact the Rocky Mountain Institute and contract with them for their advice in consulting on the Quadrennial Energy Review. Sincerely, William Wharton Smith III

  16. Issues in midterm analysis and forecasting 1998

    SciTech Connect

    1998-07-01

    Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.

  17. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint

    SciTech Connect

    Zhang, J.; Hodge, B. M.; Gomez-Lazaro, E.; Lovholm, A. L.; Berge, E.; Miettinen, J.; Holttinen, H.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Dobschinski, J.

    2013-10-01

    One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

  18. February 8, 2014: Prof. William C. Jones, Princeton University: Uncovering

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    our Cosmic Origins: What We Know, What We Can Know, and What Limits We May Face. | Princeton Plasma Physics Lab February 8, 2014, 9:30am to 11:00am Science On Saturday MBG Auditorium February 8, 2014: Prof. William C. Jones, Princeton University: Uncovering our Cosmic Origins: What We Know, What We Can Know, and What Limits We May Face. Professor William Jones, Assistant Professor of Physics Princeton University, Department of Physics Presentation: PDF icon Presentation Abstract: PDF icon 05

  19. Baseline and Target Values for PV Forecasts: Toward Improved...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting ... Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting Jie ...

  20. KST Coatings, A Business Unit of The Sherwin-Williams Company...

    OpenEI (Open Energy Information) [EERE & EIA]

    KST Coatings, A Business Unit of The Sherwin-Williams Company Jump to: navigation, search Name: KST Coatings, A Business Unit of The Sherwin-Williams Company Address: 101Prospect...

  1. Using Wikipedia to forecast diseases

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Using Wikipedia to forecast diseases Using Wikipedia to forecast diseases Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of Wikipedia articles. November 13, 2014 Del Valle and her team observe findings from their research on disease patterns from analyzing Wikipedia articles. Del Valle and her team observe findings from their research on disease patterns from analyzing Wikipedia articles. Contact Nancy Ambrosiano Communications Office (505)

  2. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect

    Lew, D.

    2011-04-01

    This presentation describes the importance of good forecasting for variable generation, the different approaches used by industry, and the importance of validated high-quality data.

  3. Forecast Energy | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Zip: 94965 Region: Bay Area Sector: Services Product: Intelligent Monitoring and Forecasting Services Year Founded: 2010 Website: www.forecastenergy.net Coordinates:...

  4. The forecast calls for flu

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Science on the Hill: The forecast calls for flu Using mathematics, computer programs, ... We're getting close. Using mathematics, computer programs, statistics and information ...

  5. U.S. Regional Demand Forecasts Using NEMS and GIS

    SciTech Connect

    Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

    2005-07-01

    The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

  6. EA-208 Williams Energy Marketing and Trading Company | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    8 Williams Energy Marketing and Trading Company EA-208 Williams Energy Marketing and Trading Company Order authorizing Williams Energy Marketing and Trading Company to export electric energy to Mexico. EA-208 Williams Energy Marketing and Trading Company (15.29 KB) More Documents & Publications EA-184 Morgan Stanley Capital Group Inc. EA-166 Duke Energy Trading and Marketing, L.L.C EA-167 PG&E Energy Trading-Power, L.P

  7. New Whole-House Solutions Case Study: Tommy Williams Homes, Longleaf Village & Belmont, Gainesville, FL

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    The market has spoken. Energy efficiency sells," said Todd Louis, vice-president of Tommy Williams Homes in Gainesville, Florida. Since partnering with the U.S. Department of Energy's Building America program in 2004, Tommy Williams' production homes have outsold the competition, with sales increasing year after year in spite of the recession. All Tommy Williams' homes achieve HERS scores of under 60, while homes built to Florida's state energy code have scores as high as 85. Tommy Williams

  8. Best Practices Case Study: Tommy Williams Homes -Gainesville, FL

    SciTech Connect

    none,

    2011-04-01

    Case study of Tommy Williams Homes who has continued to outsell the competition with sales increasing despite the recession thanks to a systems-engineering approach developed with DOE’s Building America that yields high energy efficiency, comfort, and indoor air quality. The company offers to pay buyers’ energy bills for the first year.

  9. NREL: Transmission Grid Integration - Issues Affecting Renewable...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Variability of renewable energy sources Integration costs Frequency response Emissions System balancing Energy storage Transmission Solar and wind forecasting High-penetration ...

  10. A survey on wind power ramp forecasting.

    SciTech Connect

    Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J.

    2011-02-23

    The increasing use of wind power as a source of electricity poses new challenges with regard to both power production and load balance in the electricity grid. This new source of energy is volatile and highly variable. The only way to integrate such power into the grid is to develop reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly variable at several different timescales: sub-hourly, hourly, daily, and seasonally. Wind energy, like other electricity sources, must be scheduled. Although wind power forecasting methods are used, the ability to predict wind plant output remains relatively low for short-term operation. Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, wind power's variability can present substantial challenges when large amounts of wind power are incorporated into a grid system. A critical issue is ramp events, which are sudden and large changes (increases or decreases) in wind power. This report presents an overview of current ramp definitions and state-of-the-art approaches in ramp event forecasting.

  11. Solar Energy Market Forecast | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast AgencyCompany Organization: United States Department of Energy Sector:...

  12. Upcoming Funding Opportunity for Wind Forecasting Improvement...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Wind Forecasting Improvement Project in Complex Terrain Upcoming Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain February 12, 2014 - 10:47am ...

  13. Intermediate future forecasting system

    SciTech Connect

    Gass, S.I.; Murphy, F.H.; Shaw, S.H.

    1983-12-01

    The purposes of the Symposium on the Department of Energy's Intermediate Future Forecasting System (IFFS) were: (1) to present to the energy community details of DOE's new energy market model IFFS; and (2) to have an open forum in which IFFS and its major elements could be reviewed and critiqued by external experts. DOE speakers discussed the total system, its software design, and the modeling aspects of oil and gas supply, refineries, electric utilities, coal, and the energy economy. Invited experts critiqued each of these topics and offered suggestions for modifications and improvement. This volume documents the proceedings (papers and discussion) of the Symposium. Separate abstracts have been prepared for each presentation for inclusion in the Energy Data Base.

  14. Economic Evaluation of Short-Term Wind Power Forecasts in ERCOT: Preliminary Results; Preprint

    SciTech Connect

    Orwig, K.; Hodge, B. M.; Brinkman, G.; Ela, E.; Milligan, M.; Banunarayanan, V.; Nasir, S.; Freedman, J.

    2012-09-01

    Historically, a number of wind energy integration studies have investigated the value of using day-ahead wind power forecasts for grid operational decisions. These studies have shown that there could be large cost savings gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter-term (0 to 6-hour-ahead) wind power forecasts. In 2010, the Department of Energy and National Oceanic and Atmospheric Administration partnered to fund improvements in short-term wind forecasts and to determine the economic value of these improvements to grid operators, hereafter referred to as the Wind Forecasting Improvement Project (WFIP). In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined, then the economic results of a production cost model simulation are analyzed.

  15. Microsoft PowerPoint - Williams_Profilers.ppt

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    0-MHz Profiler Rain Gauges Joss Waldvogel Disdrometers 2835-MHz Profiler Status of Profiler and Surface Data Sets for TWPICE Christopher.R.Williams@noaa.gov - University of Colorado at Boulder and NOAA Earth Science Research Laboratory Funding is from the NASA TRMM & GPM Programs through the former NOAA Aeronomy Laboratory and from the Australian Bureau of Meteorology Research Centre (BMRC) Approximately 8 km between ARM and Profiler sites The profiler and surface observations deployed at

  16. William Rees appointed to new Global Security leadership position

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Global security leadership position William Rees appointed to new Global Security leadership position A new position that elevates the importance of the Lab's work in key program areas, including non-proliferation, intelligence support, defense, nuclear counterterrorism, and homeland security. June 16, 2009 Los Alamos National Laboratory sits on top of a once-remote mesa in northern New Mexico with the Jemez mountains as a backdrop to research and innovation covering multi-disciplines from

  17. Dr. William Tumas - Associate Laboratory Director, Materials and Chemical

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Science and Technology | NREL Dr. William Tumas - Associate Laboratory Director, Materials and Chemical Science and Technology A photo of Bill Tumas Bill Tumas is responsible for overall leadership, management, technical direction, and workforce development of the materials and chemical science and technology capabilities at NREL, spanning fundamental and applied R&D for renewable energy and energy efficiency. Key program areas include solar energy conversion for electricity and fuels,

  18. Science on Tap - Forecasting illness

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Science on Tap - Forecasting illness Science on Tap - Forecasting illness WHEN: Mar 17, 2016 5:30 PM - 7:00 PM WHERE: UnQuarked Wine Room 145 Central Park Square, Los Alamos, New Mexico 87544 USA CONTACT: Linda Anderman (505) 665-9196 CATEGORY: Bradbury INTERNAL: Calendar Login Event Description Mark your calendars for this event held every third Thursday from 5:30 to 7 p.m. A short presentation is followed by a lively discussion on a different subject each month. Forecasting the flu (and other

  19. Acquisition Forecast Download | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Acquisition Forecast Download Acquisition Forecast Download Click on the link to download a copy of the DOE HQ Acquisition Forecast. Acquisition-Forecast-2016-11-10.xlsx (70.03 KB) More Documents & Publications National Nuclear Security Administration - Juliana Heynes Small Business Program Manager Directory EA-1900: Notice of Availability of a Draft Environmental Assessment

  20. Celebrating the Legacy of Bioenergy Director Lt. Col. William C. Holmberg |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Celebrating the Legacy of Bioenergy Director Lt. Col. William C. Holmberg Celebrating the Legacy of Bioenergy Director Lt. Col. William C. Holmberg October 18, 2016 - 4:52pm Addthis By Jonathan Male, Director of the Bioenergy Technologies Office The U.S. Department of Energy's (DOE's) Bioenergy Technologies Office (BETO) recognizes the foundational accomplishments of retired Marine Lieutenant Colonel William C. Holmberg, the founding director of DOE bioenergy efforts and

  1. Little Boy weaponeer William "Deak" Parsons, wartime Los Alamos

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    division leader, focus of next 70th anniversary lecture 70th anniversary lecture Little Boy weaponeer William "Deak" Parsons, wartime Los Alamos division leader, focus of next 70th anniversary lecture Former Laboratory historian Roger Meade to present lecture. August 8, 2013 William S. "Deak" Parsons William S. "Deak" Parsons Contact Steve Sandoval Communications Office (505) 665-9206 Email Josh Dolin Communications Office (505) 665-4803 Email Meade said Los

  2. Buildng America Whole-House Solutions for New Homes: William Ryan Homes,

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Tampa, Florida | Department of Energy Buildng America Whole-House Solutions for New Homes: William Ryan Homes, Tampa, Florida Buildng America Whole-House Solutions for New Homes: William Ryan Homes, Tampa, Florida Case study of William Ryan Homes, who worked with Building America research partner CARB to design HERS-65 homes with energy-efficient heat pumps and programmable thermostats with humidity controls, foam-filled concrete block walls, draining house wrap, and airsealed kneewalls.

  3. Building America Whole-House Solutions for New Homes: Tommy Williams...

    Energy.gov [DOE] (indexed site)

    Building America Efficient Solutions for New Homes Case Study: Tommy Williams Homes Initial Performance of Two Zero Energy Homes, Gainesville, Florida Building America Best ...

  4. William Dorland, 2009 | U.S. DOE Office of Science (SC)

    Office of Science (SC)

    William Dorland, 2009 Print Text Size: A A A FeedbackShare Page Nuclear Technologies (Fission and Fusion): For the development of comprehensive computer simulations of plasma ...

  5. Modeling-Computer Simulations At U.S. West Region (Williams ...

    OpenEI (Open Energy Information) [EERE & EIA]

    navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Modeling-Computer Simulations At U.S. West Region (Williams & Deangelo, 2008) Exploration Activity...

  6. Building America Whole-House Solutions for New Homes: Tommy Williams Homes,

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Gainesville, Florida | Department of Energy Tommy Williams Homes, Gainesville, Florida Building America Whole-House Solutions for New Homes: Tommy Williams Homes, Gainesville, Florida Case study of Tommy Williams Homes who partnered with Building America to build HERS-58 homes with foam gaskets at sill and top plates, fresh air intakes, SEER 16/HSPF 9.5 heat pumps, and tight air sealing of 2.7 ACH50. Tommy Williams Homes: Longleaf Village & Belmont - Gainesville, FL (671.55 KB) More

  7. 10 CFR 850, Request for Information- Docket Number: HS-RM-10-CBDPP- William R. Kleem

    Energy.gov [DOE]

    Commenter: William R. Kleem 10 CFR 850 - Request for Information Docket Number: HS-RM-10-CBDPP Comment Close Date: 2/22/2011

  8. CHARACTERIZATION SURVEY OF THE BAKER AND WILLIAMS WAREHOUSES

    Office of Legacy Management (LM)

    CHARACTERIZATION SURVEY OF THE BAKER AND WILLIAMS WAREHOUSES BUILDING 513-519 NEW YORK, NEW YORK Prepared by W. C. Adams Environmental Survey and Site Assessment Program Energy/Environment System Division Oak Ridge Institute for Science and Education Oak Ridge, Tennessee 37831-0117 Prepared for the Office of Environmental Restoration U.S. Department of Energy FINAL REPORT DECEMBER 1993 This report is based on work performed under contract number DE-AC05-760R00033 with the U.S. Department of

  9. VERIFICATION SURVEY OF THE BAKER AND WILLIAMS WAREHOUSES

    Office of Legacy Management (LM)

    ,~ *-,-' .r_~, VERIFICATION SURVEY OF THE BAKER AND WILLIAMS WAREHOUSES BUILDING 513-519 NEW YORK, NEW YORK Prepared by W. C. Adams Environmental Survey and Site Assessment Program Energy/Environment Systems Division Oak Ridge Institute for Science and Education Oak Ridge, Tennessee 37831-0117 Prepared for the Office of Environmental Restoration U.S. Department of Energy FINAL REPORT JUNE 1994 This report is based on work performed under contract number DE-AC05-760R00033 with the U.S. Department

  10. Wind Forecast Improvement Project Southern Study Area Final Report...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern ...

  11. Picture of the Week: Forecasting Flu

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    3 Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? March 6, 2016 flu epidemics modellled using social media Watch the video on YouTube. Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? Using real-time data from Wikipedia and social media, Sara del

  12. EIA lowers forecast for summer gasoline prices

    Energy Information Administration (EIA) (indexed site)

    EIA lowers forecast for summer gasoline prices U.S. gasoline prices are expected to be ... according to the new monthly forecast from the U.S. Energy Information Administration. ...

  13. Wind Forecasting Improvement Project | Department of Energy

    Energy Saver

    Forecasting Improvement Project Wind Forecasting Improvement Project October 3, 2011 - 12:12pm Addthis This is an excerpt from the Third Quarter 2011 edition of the Wind Program ...

  14. W&M, JLab Host International Neutrino Workshop (William & Mary News &

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Events) | Jefferson Lab W&M, JLab Host International Neutrino Workshop (William & Mary News & Events) External Link: http://www.wm.edu/news/stories/2012/william--mary-hosts-international-neutrino-w... By jlab_admin on Thu, 2012-07-19

  15. Recent Trends in Variable Generation Forecasting and Its Value to the Power System

    DOE PAGES [OSTI]

    Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; Sharp, Justin; Wilczak, James M.; Freedman, Jeffrey; Haupt, Sue Ellen; Cline, Joel; Bartholomy, Obadiah; Hamann, Hendrik F.; et al

    2014-12-23

    We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value ofmore » adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.« less

  16. Recent Trends in Variable Generation Forecasting and Its Value to the Power System

    SciTech Connect

    Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; Sharp, Justin; Wilczak, James M.; Freedman, Jeffrey; Haupt, Sue Ellen; Cline, Joel; Bartholomy, Obadiah; Hamann, Hendrik F.; Hodge, Bri-Mathias; Finley, Catherine; Nakafuji, Dora; Peterson, Jack L.; Maggio, David; Marquis, Melinda

    2014-12-23

    We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value of adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.

  17. Forecasting Water Quality & Biodiversity

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Forecasting Water Quality & Biodiversity March 25, 2015 Cross-cutting Sustainability Platform Review Principle Investigator: Dr. Henriette I. Jager Organization: Oak Ridge National Laboratory This presentation does not contain any proprietary, confidential, or otherwise restricted information 2015 DOE Bioenergy Technologies Office (BETO) Project Peer Review Goal Statement Addresses the following MYPP BETO goals:  Advance scientific methods and models for measuring and understanding

  18. ALCF Future Systems Tim Williams, Argonne Leadership Computing Facility

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Future Systems Tim Williams, Argonne Leadership Computing Facility DOE Exascale Requirements Review: High Energy Physics June 11, 2015 Production Systems (ALCF-2) 2 Mira - IBM Blue Gene/Q ¥ 49,152 nodes ¡ PowerPC A2 cpu - 16 cores, 4 HW threads/core ¡ 16 GB RAM ¥ Aggregate ¡ 768 TB RAM, 768K cores ¡ Peak 10 PetaFLOPS ¥ 5D torus interconnect Cooley - Viz/Analysis cluster ¥ 126 nodes: ¡ Two 2.4 GHz Intel Haswell 6-core - 384 GB RAM ¡ NVIDIA Tesla K80 (two

  19. Plant improvements extend life of McWilliams Station

    SciTech Connect

    Meyer, R.; Balsbaugh, R.; Korinek, K.

    1995-12-31

    A combined-cycle conversion project at Alabama Electric Cooperative (AEC) will extend the life of its gas- and coal-fired McWilliams Station. The conversion will allow the plant to generate power for the next 30 years and boost its system intermediate and peaking capacity. Station capacity will increase from 42 MW to 151 MW (net), and the heat rate will improve from 15,000 to 9,000 Btu/kW-hr (HHV). Thanks to AEC`s preventive maintenance program, overhauls to the equipment remaining in service were unnecessary. Except for slight modifications, most systems will remain as they have for the last 40 years. This paper will describe the plant`s original construction and the changes made to sustain it.

  20. Forecasting Wind and Solar Generation: Improving System Operations, Greening the Grid

    SciTech Connect

    Tian; Tian; Chernyakhovskiy, Ilya

    2016-01-01

    This document discusses improving system operations with forecasting and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.

  1. An Optimized Autoregressive Forecast Error Generator for Wind and Load Uncertainty Study

    SciTech Connect

    De Mello, Phillip; Lu, Ning; Makarov, Yuri V.

    2011-01-17

    This paper presents a first-order autoregressive algorithm to generate real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast errors. The methodology aims at producing random wind and load forecast time series reflecting the autocorrelation and cross-correlation of historical forecast data sets. Five statistical characteristics are considered: the means, standard deviations, autocorrelations, and cross-correlations. A stochastic optimization routine is developed to minimize the differences between the statistical characteristics of the generated time series and the targeted ones. An optimal set of parameters are obtained and used to produce the RT, HA, and DA forecasts in due order of succession. This method, although implemented as the first-order regressive random forecast error generator, can be extended to higher-order. Results show that the methodology produces random series with desired statistics derived from real data sets provided by the California Independent System Operator (CAISO). The wind and load forecast error generator is currently used in wind integration studies to generate wind and load inputs for stochastic planning processes. Our future studies will focus on reflecting the diurnal and seasonal differences of the wind and load statistics and implementing them in the random forecast generator.

  2. Use of wind power forecasting in operational decisions.

    SciTech Connect

    Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V.

    2011-11-29

    The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help

  3. Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint

    SciTech Connect

    Florita, A.; Hodge, B. M.; Milligan, M.

    2012-08-01

    The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites and for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.

  4. Roy Williams and others ? keys to Y-12s success Or: People...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    in The Oak Ridger) Gordon Fee sent me an e-mail on December 23, 2009, noting that Roy Williams had just died. He went on to say that he sure hoped the history of Y-12 would include...

  5. William A. Lokke, 1975 | U.S. DOE Office of Science (SC)

    Office of Science (SC)

    William A. Lokke, 1975 Print Text Size: A A A FeedbackShare Page Weapons: For original and creative computer calculations of nuclear weapon outputs, for the development of methods ...

  6. FIA-12-0049- In the Matter of William B. Ray

    Energy.gov [DOE]

    On October 1, 2012, OHA denied an Appeal filed by William B. Ray under the Freedom of Information and Privacy Act.  Mr. Ray was appealing from a determination issued by the DOE’s Oak Ridge Office ...

  7. Best Practices Case Study: William Ryan House - Tampa Division, Tampa, FL

    SciTech Connect

    none,

    2011-04-01

    Case study of William Ryan Homes, who cut energy use to achieve HERS scores of 65 to 70 on nine floor plans that will be featured in 277 homes in central Florida.

  8. Redelegation/Designation Order No. 00-022.02A to William C. Gibson...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    No. 00-022.02A to William C. Gibson, Jr as Head of Contracting Activity (HCA) for the Strategic Petroleum Reserve Project Management Office by johnsonmd Functional areas:...

  9. William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) | U.S.

    Office of Science (SC)

    DOE Office of Science (SC) William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) Biological and Environmental Research (BER) BER Home About Research Biological Systems Science Division (BSSD) Climate and Environmental Sciences Division (CESD) ARM Climate Research Facility Atmospheric System Research (ASR) Program Climate Model Development and Validation (CMDV) Data Management Earth System Modeling (ESM) Program William R. Wiley Environmental Molecular Sciences Laboratory (EMSL)

  10. The Value of Wind Power Forecasting

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Wind Power Forecasting Preprint Debra Lew and Michael Milligan National Renewable Energy Laboratory Gary Jordan and Richard Piwko GE Energy Presented at the 91 st American ...

  11. NREL: Resource Assessment and Forecasting Home Page

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    are used to plan and develop renewable energy technologies and support climate change research. Learn more about NREL's resource assessment and forecasting research:...

  12. Funding Opportunity Announcement for Wind Forecasting Improvement...

    Energy.gov [DOE] (indexed site)

    There is no cost to participate and all applicants are encouraged to attend. To join the ... Related Articles Upcoming Funding Opportunity for Wind Forecasting Improvement Project in ...

  13. Module 6 - Metrics, Performance Measurements and Forecasting...

    Energy.gov [DOE] (indexed site)

    This module reviews metrics such as cost and schedule variance along with cost and schedule performance indices. In addition, this module will outline forecasting tools such as ...

  14. Development and Demonstration of Advanced Forecasting, Power...

    Energy.gov [DOE] (indexed site)

    Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices 63wateruseoptimizationprojectanlgasper.ppt (7.72 MB) More ...

  15. NREL: Resource Assessment and Forecasting - Webmaster

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    email address: Your message: Send Message Printable Version Resource Assessment & Forecasting Home Capabilities Facilities Working with Us Research Staff Data & Resources Did...

  16. Forecast and Funding Arrangements - Hanford Site

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Annual Waste Forecast and Funding Arrangements About Us Hanford Site Solid Waste Acceptance Program What's New Acceptance Criteria Acceptance Process Becoming a new Hanford...

  17. Sensing, Measurement, and Forecasting | Grid Modernization | NREL

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Sensing, Measurement, and Forecasting NREL measures weather resources and power systems, forecasts renewable resources and grid conditions, and converts measurements into operational intelligence to support a modern grid. Photo of solar resource monitoring equipment Modernizing the grid involves assessing its health in real time, predicting its behavior and potential disruptions, and quickly responding to events-which requires understanding vital parameters throughout the electric

  18. Toward a science of tumor forecasting for clinical oncology

    DOE PAGES [OSTI]

    Yankeelov, Thomas E.; Quaranta, Vito; Evans, Katherine J.; Rericha, Erin C.

    2015-03-15

    We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapiesmore » is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. Furthermore, with a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.« less

  19. Toward a science of tumor forecasting for clinical oncology

    SciTech Connect

    Yankeelov, Thomas E.; Quaranta, Vito; Evans, Katherine J.; Rericha, Erin C.

    2015-03-15

    We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. Furthermore, with a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.

  20. Towards a Science of Tumor Forecast for Clinical Oncology

    DOE PAGES [OSTI]

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoplymore » of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.« less

  1. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.

  2. Study forecasts disappearance of conifers due to climate change

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Study forecasts disappearance of conifers due to climate change Study forecasts disappearance of conifers due to climate change New results, reported in a paper released today in ...

  3. Data Collection and Comparison with Forecasted Unit Sales of...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types PDF icon Data Collection ...

  4. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen MJ ... Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen, ...

  5. Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Metrics for Evaluating the Accuracy of Solar Power Forecasting Preprint J. Zhang, B.-M. Hodge, and A. Florita National Renewable Energy Laboratory S. Lu and H. F. Hamann IBM TJ Watson Research Center V. Banunarayanan U.S. Department of Energy To be presented at 3rd International Workshop on Integration of Solar Power into Power Systems London, England October 21 - 22, 2013 Conference Paper NREL/CP-5500-60142 October 2013 NOTICE The submitted manuscript has been offered by an employee of the

  6. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.

    SciTech Connect

    United States. Bonneville Power Administration.

    1994-02-01

    This publication documents the load forecast scenarios and assumptions used to prepare BPA`s Whitebook. It is divided into: intoduction, summary of 1993 Whitebook electricity demand forecast, conservation in the load forecast, projection of medium case electricity sales and underlying drivers, residential sector forecast, commercial sector forecast, industrial sector forecast, non-DSI industrial forecast, direct service industry forecast, and irrigation forecast. Four appendices are included: long-term forecasts, LTOUT forecast, rates and fuel price forecasts, and forecast ranges-calculations.

  7. Largest On-Campus Solar Facility Being Installed at William Paterson |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Largest On-Campus Solar Facility Being Installed at William Paterson Largest On-Campus Solar Facility Being Installed at William Paterson March 29, 2010 - 10:57am Addthis Paul Lester Paul Lester Digital Content Specialist, Office of Public Affairs What does this project do? Solar arrays at parking lots and photovoltaic cells on the rooftops of campus buildings should provide about 15 to 20 percent of our energy needs on the campus. Cranes place solar panels on roofs and

  8. A parable of oil and water: Revisiting Prince William Sound, four years after

    SciTech Connect

    Keeble, J.

    1993-12-31

    On Good Friday, March 24, 1989, the Exxon oil tanker Valdez foundered on Bligh Reef, spilling 11 million gallons of crude oil into Alaska`s Prince William Sound. To Alaskans, especially fishing people, this was a shocking but not entirely unanticipated event, as there had been several near misses in the twelve years since the opening of oil shipping from Valdez, Alaska. This article revisits Prince William sound to evaluate both the lingering environmental effects and the socio-economic effects of the spill and the huge monetary settlement from the spills.

  9. Edward William Larsen, 1994 | U.S. DOE Office of Science (SC)

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Edward William Larsen, 1994 The Ernest Orlando Lawrence Award Lawrence Award Home Nomination & Selection Guidelines Award Laureates 2010's 2000's 1990's 1980's 1970's 1960's Ceremony The Life of Ernest Orlando Lawrence Contact Information The Ernest Orlando Lawrence Award U.S. Department of Energy SC-2/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-2411 E: Email Us 1990's Edward William Larsen, 1994 Print Text Size: A A A FeedbackShare Page Nuclear

  10. F. William Studier, 1977 | U.S. DOE Office of Science (SC)

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    F. William Studier, 1977 The Ernest Orlando Lawrence Award Lawrence Award Home Nomination & Selection Guidelines Award Laureates 2010's 2000's 1990's 1980's 1970's 1960's Ceremony The Life of Ernest Orlando Lawrence Contact Information The Ernest Orlando Lawrence Award U.S. Department of Energy SC-2/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-2411 E: Email Us 1970's F. William Studier, 1977 Print Text Size: A A A FeedbackShare Page Life Sciences: For

  11. Why Did the Electron Cross the Solar Cell? William Tisdale Knows | U.S. DOE

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Office of Science (SC) Why Did the Electron Cross the Solar Cell? William Tisdale Knows News News Home Featured Articles 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 Science Headlines Science Highlights Presentations & Testimony News Archives Communications and Public Affairs Contact Information Office of Science U.S. Department of Energy 1000 Independence Ave., SW Washington, DC 20585 P: (202) 586-5430 05.16.16 Why Did the Electron Cross the Solar Cell? William Tisdale

  12. OSTIblog Posts by Dr. William Watson | OSTI, US Dept of Energy Office of

    Office of Scientific and Technical Information (OSTI)

    Scientific and Technical Information Dr. William Watson Dr. William Watson's picture Physicist Mars Science Laboratory Curiosity - ChemCam 4265 Caltech.png Mars Science Laboratory Curiosity - ChemCam Read more about 4265 Science Communications Published on Sep 12, 2012 How do you run chemical tests at a geologic site millions of miles away from you to see what the rocks and soil are made of? Curiosity's new instrument ChemCam, developed at Los Alamos National Laboratory, is designed to

  13. Metrics for Evaluating the Accuracy of Solar Power Forecasting (Presentation)

    SciTech Connect

    Zhang, J.; Hodge, B.; Florita, A.; Lu, S.; Hamann, H.; Banunarayanan, V.

    2013-10-01

    This presentation proposes a suite of metrics for evaluating the performance of solar power forecasting.

  14. Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)

    SciTech Connect

    Hodge, B. M.; Ela, E.; Milligan, M.

    2011-10-01

    This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.

  15. Offshore Lubricants Market Forecast | OpenEI Community

    OpenEI (Open Energy Information) [EERE & EIA]

    Offshore Lubricants Market Forecast Home There are currently no posts in this category. Syndicate...

  16. Coal Fired Power Generation Market Forecast | OpenEI Community

    OpenEI (Open Energy Information) [EERE & EIA]

    Coal Fired Power Generation Market Forecast Home There are currently no posts in this category. Syndicate...

  17. Flood Forecasting in River System Using ANFIS

    SciTech Connect

    Ullah, Nazrin; Choudhury, P.

    2010-10-26

    The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.

  18. ARM - CARES - Tracer Forecast for CARES

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    News & Press Backgrounder (PDF, 1.45MB) G-1 Aircraft Fact Sheet (PDF, 1.3MB) Contacts Rahul Zaveri, Lead Scientist Tracer Forecasts for CARES This webpage contains 72-hr...

  19. Text-Alternative Version LED Lighting Forecast

    Energy.gov [DOE]

    The DOE report Energy Savings Forecast of Solid-State Lighting in General Illumination Applications estimates the energy savings of LED white-light sources over the analysis period of 2013 to 2030....

  20. energy data + forecasting | OpenEI Community

    OpenEI (Open Energy Information) [EERE & EIA]

    energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in...

  1. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect

    Brainard, James Robert

    2009-10-01

    This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

  2. AVLIS: a technical and economic forecast

    SciTech Connect

    Davis, J.I.; Spaeth, M.L.

    1986-01-01

    The AVLIS process has intrinsically large isotopic selectivity and hence high separative capacity per module. The critical components essential to achieving the high production rates represent a small fraction (approx.10%) of the total capital cost of a production facility, and the reference production designs are based on frequent replacement of these components. The specifications for replacement frequencies in a plant are conservative with respect to our expectations; it is reasonable to expect that, as the plant is operated, the specifications will be exceeded and production costs will continue to fall. Major improvements in separator production rates and laser system efficiencies (approx.power) are expected to occur as a natural evolution in component improvements. With respect to the reference design, such improvements have only marginal economic value, but given the exigencies of moving from engineering demonstration to production operations, we continue to pursue these improvements in order to offset any unforeseen cost increases. Thus, our technical and economic forecasts for the AVLIS process remain very positive. The near-term challenge is to obtain stable funding and a commitment to bring the process to full production conditions within the next five years. If the funding and commitment are not maintained, the team will disperse and the know-how will be lost before it can be translated into production operations. The motivation to preserve the option for low-cost AVLIS SWU production is integrally tied to the motivation to maintain a competitive nuclear option. The US industry can certainly survive without AVLIS, but our tradition as technology leader in the industry will certainly be lost.

  3. Key Neutrino behavior observed at Daya Bay (The College of William and

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Mary) | Jefferson Lab Key Neutrino behavior observed at Daya Bay (The College of William and Mary) External Link: http://www.wm.edu/news/stories/2012/key-neutrino-behavior-observed-at-daya-bay-1... By jlab_admin on Thu, 2012-03-08

  4. Eastern Renewable Generation Integration Study Solar Dataset (Presentation)

    SciTech Connect

    Hummon, M.

    2014-04-01

    The National Renewable Energy Laboratory produced solar power production data for the Eastern Renewable Generation Integration Study (ERGIS) including "real time" 5-minute interval data, "four hour ahead forecast" 60-minute interval data, and "day-ahead forecast" 60-minute interval data for the year 2006. This presentation provides a brief overview of the three solar power datasets.

  5. 1994 Solid waste forecast container volume summary

    SciTech Connect

    Templeton, K.J.; Clary, J.L.

    1994-09-01

    This report describes a 30-year forecast of the solid waste volumes by container type. The volumes described are low-level mixed waste (LLMW) and transuranic/transuranic mixed (TRU/TRUM) waste. These volumes and their associated container types will be generated or received at the US Department of Energy Hanford Site for storage, treatment, and disposal at Westinghouse Hanford Company`s Solid Waste Operations Complex (SWOC) during a 30-year period from FY 1994 through FY 2023. The forecast data for the 30-year period indicates that approximately 307,150 m{sup 3} of LLMW and TRU/TRUM waste will be managed by the SWOC. The main container type for this waste is 55-gallon drums, which will be used to ship 36% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of 55-gallon drums is Past Practice Remediation. This waste will be generated by the Environmental Restoration Program during remediation of Hanford`s past practice sites. Although Past Practice Remediation is the primary generator of 55-gallon drums, most waste generators are planning to ship some percentage of their waste in 55-gallon drums. Long-length equipment containers (LECs) are forecasted to contain 32% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of LECs is the Long-Length Equipment waste generator, which is responsible for retrieving contaminated long-length equipment from the tank farms. Boxes are forecasted to contain 21% of the waste. These containers are primarily forecasted for use by the Environmental Restoration Operations--D&D of Surplus Facilities waste generator. This waste generator is responsible for the solid waste generated during decontamination and decommissioning (D&D) of the facilities currently on the Surplus Facilities Program Plan. The remaining LLMW and TRU/TRUM waste volume is planned to be shipped in casks and other miscellaneous containers.

  6. Integrated Assessment of Global Climate Change | U.S. DOE Office of Science

    Office of Science (SC)

    (SC) Integrated Assessment of Global Climate Change Biological and Environmental Research (BER) BER Home About Research Biological Systems Science Division (BSSD) Climate and Environmental Sciences Division (CESD) ARM Climate Research Facility Atmospheric System Research (ASR) Program Climate Model Development and Validation (CMDV) Data Management Earth System Modeling (ESM) Program William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) Integrated Assessment of Global Climate

  7. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

    SciTech Connect

    Zhang, Jie; Hodge, Bri -Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat; Black, Jon; Tedesco, John

    2015-11-10

    Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.

  8. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

    DOE PAGES [OSTI]

    Zhang, Jie; Hodge, Bri -Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat; Black, Jon; Tedesco, John

    2015-11-10

    Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based onmore » state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.« less

  9. The Value of Improved Short-Term Wind Power Forecasting

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    ... up-ramp reserves c down cost in MWh of down-ramp reserves R down MW range for ... power forecasting and the increased gas usage that comes with less-accurate forecasting. ...

  10. DOE Taking Wind Forecasting to New Heights | Department of Energy

    Energy Saver

    Taking Wind Forecasting to New Heights DOE Taking Wind Forecasting to New Heights May 18, 2015 - 3:24pm Addthis A 2013 study conducted for the U.S. Department of Energy (DOE) by ...

  11. Solar Forecasting Gets a Boost from Watson, Accuracy Improved...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am Addthis IBM ...

  12. PBL FY 2003 Second Quarter Review Forecast of Generation Accumulated...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    the rate period (i.e., FY 2002-2006), a forecast of that end-of-year Accumulated Net Revenue (ANR) will be completed. If the ANR at the end of the forecast year falls below the...

  13. Regional four-dimensional variational data assimilation in a quasi-operational forecasting environment

    SciTech Connect

    Zupanski, M. )

    1993-08-01

    Four-dimensional variational data assimilation is applied to a regional forecast model as part of the development of a new data assimilation system at the National Meteorological Center (NMC). The assimilation employs an operational version of the NMC's new regional forecast model defined in eta vertical coordinates, and data used are operationally produced optimal interpolation (OI) analyses (using the first guess from the NMC's global spectral model), available every 3 h. Humidity and parameterized processes are not included in the adjoint model integration. The calculation of gradients by the adjoint model is approximate since the forecast model is used in its full-physics operational form. All experiments are over a 12-h assimilation period with subsequent 48-h forecast. Three different types of assimilation experiments are performed: (a) adjustment of initial conditions only (standard [open quotes]adjoint[close quotes] approach), (b) adjustment of a correction to the model equations only (variational continuous assimilation), and (c) simultaneous or sequential adjustment of both initial conditions and the correction term. Results indicate significantly better results when the correction term is included in the assimilation. It is shown, for a single case, that the new technique [experiment (c)] is able to produce a forecast better than the current conventional OI assimilation. It is very important to note that these results are obtained with an approximate gradient, calculated from a simplified adjoint model. Thus, it may be possible to perform an operational four-dimensional variational data assimilation of realistic forecast models, even before more complex adjoint models are developed. Also, the results suggest that it may be possible to reduce the large computational cost of assimilation by using only a few iterations of the minimization algorithm. This fast convergence is encouraging from the prospective of operational use. 37 refs., 10 figs., 1 tab.

  14. Wind Integration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Wind Generation - ScheduledActual Balancing Reserves - Deployed Near Real-time Wind Animation Wind Projects under Review Growth Forecast Fact Sheets Working together to address...

  15. Wind power forecasting in U.S. electricity markets.

    SciTech Connect

    Botterud, A.; Wang, J.; Miranda, V.; Bessa, R. J.; Decision and Information Sciences; INESC Porto

    2010-04-01

    Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts.

  16. Wind power forecasting in U.S. Electricity markets

    SciTech Connect

    Botterud, Audun; Wang, Jianhui; Miranda, Vladimiro; Bessa, Ricardo J.

    2010-04-15

    Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts. (author)

  17. Improving the Accuracy of Solar Forecasting Funding Opportunity |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Improving the Accuracy of Solar Forecasting Funding Opportunity Improving the Accuracy of Solar Forecasting Funding Opportunity Through the Improving the Accuracy of Solar Forecasting Funding Opportunity, DOE is funding solar projects that are helping utilities, grid operators, solar power plant owners, and other stakeholders better forecast when, where, and how much solar power will be produced at the desired locations in the United States. More accurate solar

  18. Combined Heat And Power Installation Market Forecast | OpenEI...

    OpenEI (Open Energy Information) [EERE & EIA]

    Combined Heat And Power Installation Market Forecast Home There are currently no posts in this category. Syndicate...

  19. ANL Software Improves Wind Power Forecasting | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ANL Software Improves Wind Power Forecasting ANL Software Improves Wind Power Forecasting May 1, 2012 - 3:19pm Addthis This is an excerpt from the Second Quarter 2012 edition of the Wind Program R&D Newsletter. Since 2008, Argonne National Laboratory and INESC TEC (formerly INESC Porto) have conducted a research project to improve wind power forecasting and better use of forecasting in electricity markets. One of the main results from the project is ARGUS PRIMA (PRediction Intelligent

  20. Wind Power Forecasting Error Distributions over Multiple Timescales (Presentation)

    SciTech Connect

    Hodge, B. M.; Milligan, M.

    2011-07-01

    This presentation presents some statistical analysis of wind power forecast errors and error distributions, with examples using ERCOT data.

  1. New Whole-House Solutions Case Study: Tommy Williams Homes Initial Performance of Two Zero Energy Homes, Gainesville, Florida

    SciTech Connect

    none,

    2011-11-01

    Tommy Williams Homes worked with PNNL, Florida HERO, Energy Smart Home Plans, and Florida Solar Energy Center to design and test two zero energy homes. Energy use was 30% lower in one home and 60% lower in the other.

  2. M E M O R A N D U M To: DOE Office of General Counsel From: William...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Present for APGA were Dave Schryver and Dan Lapato and its General Counsel, William T. Miller of McCarter & English, LLP. Present for DOE were John Cymbalski and Dan Cohen. The ...

  3. OSTIblog Articles in the William Watson Topic | OSTI, US Dept of Energy

    Office of Scientific and Technical Information (OSTI)

    Office of Scientific and Technical Information William Watson Topic Plasmas - The Greatest Show on Earth by Kathy Chambers 24 Jun, 2013 in Products and Content Perhaps the most beautiful and eerie displays of light in our sky are a phenomenon known as the auroras. This natural glow of light in the sky in high latitude regions usually displays ribbons of colors from a fluorescent green to brilliant purple to a vivid crimson somewhat like an unexpected beautiful sunrise or sunset. Observers

  4. Essential Role in Modern Science William E. Johnston, ESnet Adviser and Senior Scientist

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Evolution of Research and Education Networks and their Essential Role in Modern Science William E. Johnston, ESnet Adviser and Senior Scientist Chin Guok, Evangelos Chaniotakis, Kevin Oberman, Eli Dart, Joe Metzger and Mike O'Conner, Core Engineering, Brian Tierney, Advanced Development, Mike Helm and Dhiva Muruganantham, Federated Trust Steve Cotter, Department Head wej@es.net, this talk is available at www.es.net Energy Sciences Network Lawrence Berkeley National Laboratory Networking for the

  5. TESTIMONY OF WILLIAM S. MAHARAY DEPUTY INSPECTOR GENERAL FOR AUDIT SERVICES

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    TESTIMONY OF WILLIAM S. MAHARAY DEPUTY INSPECTOR GENERAL FOR AUDIT SERVICES U.S. DEPARTMENT OF ENERGY WASHINGTON D.C. BEFORE THE SUBCOMMITTEE ON GOVERNMENT MANAGEMENT, ORGANIZATION AND PROCUREMENT COMMITTEE ON OVERSIGHT AND GOVERNMENT REFORM U.S. HOUSE OF REPRESENTATIVES MARCH 20,2007 Mr. Chairman and members of the Subcommittee, I am pleased to be here at your request to testify on issues associated with the FY 2005 and 2006 Audits of the Department of Energy's Financial Statements. Over the

  6. Interview with Dr. William F. Brinkman offers insights on Energy Department

    Office of Scientific and Technical Information (OSTI)

    directions, R&D | OSTI, US Dept of Energy Office of Scientific and Technical Information Interview with Dr. William F. Brinkman offers insights on Energy Department directions, R&D Back to the OSTI News Listing for 2012 In its "Trailblazers of North American Research" edition, International Innovation explores a spectrum of groundbreaking research and development activities, including those at the nation's largest supporter of basic research in the physical sciences - the

  7. Speakers: Eric M. Lightner, U.S. Department of Energy William M. Gausman, Pepco Holdings, Inc.

    Gasoline and Diesel Fuel Update

    8: "Smart Grid: Impacts on Electric Power Supply and Demand" Speakers: Eric M. Lightner, U.S. Department of Energy William M. Gausman, Pepco Holdings, Inc. Christian Grant, Booz & Company, Inc. F. Michael Valocchi, IBM Global Business Services [Note: Recorders did not pick up introduction of panel (see biographies for details on the panelists) or introduction of session.] Eric Lightner: Well, good morning, everybody. My name is Eric Lightner. I work at the U.S. Department of

  8. Issues in midterm analysis and forecasting, 1996

    SciTech Connect

    1996-08-01

    This document consists of papers which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1996. Topics include: The Potential Impact of Technological Progress on U.S. Energy Markets; The Outlook for U.S. Import Dependence; Fuel Economy, Vehicle Choice, and Changing Demographics, and Annual Energy Outlook Forecast Evaluation.

  9. Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting

    SciTech Connect

    Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat

    2015-10-05

    Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.

  10. Enhanced Short-Term Wind Power Forecasting and Value to Grid Operations: Preprint

    SciTech Connect

    Orwig, K.; Clark, C.; Cline, J.; Benjamin, S.; Wilczak, J.; Marquis, M.; Finley, C.; Stern, A.; Freedman, J.

    2012-09-01

    The current state of the art of wind power forecasting in the 0- to 6-hour time frame has levels of uncertainty that are adding increased costs and risk on the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S. Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: 1) a 1-year field measurement campaign within two regions; 2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh (HRRR) model by assimilating the data from the field campaign; and 3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provides an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis.

  11. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach

    SciTech Connect

    Brown, C. W.; Hood, Raleigh R.; Long, Wen; Jacobs, John M.; Ramers, D. L.; Wazniak, C.; Wiggert, J. D.; Wood, R.; Xu, J.

    2013-09-01

    The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as sea-surface temperature and salinity, the concentrations of chlorophyll, nitrate, and dissolved oxygen, and the likelihood of encountering several noxious species, including harmful algal blooms and water-borne pathogens, for the purpose of monitoring the Bay's ecosystem. While the physical and biogeochemical variables are forecast mechanistically using the Regional Ocean Modeling System configured for the Chesapeake Bay, the species predictions are generated using a novel mechanistic empirical approach, whereby real-time output from the coupled physical biogeochemical model drives multivariate empirical habitat models of the target species. The predictions, in the form of digital images, are available via the World Wide Web to interested groups to guide recreational, management, and research activities. Though full validation of the integrated forecasts for all species is still a work in progress, we argue that the mechanisticempirical approach can be used to generate a wide variety of short-term ecological forecasts, and that it can be applied in any marine system where sufficient data exist to develop empirical habitat models. This paper provides an overview of this system, its predictions, and the approach taken.

  12. Forecasting hotspots using predictive visual analytics approach

    SciTech Connect

    Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David

    2014-12-30

    A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

  13. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: access logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.

  14. Global disease monitoring and forecasting with Wikipedia

    DOE PAGES [OSTI]

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: accessmore » logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.« less

  15. Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting: Preprint

    SciTech Connect

    Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat

    2015-08-05

    Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output. forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.

  16. Building America Business Solutions for New Homes: Marketing Zero Energy Homes: Tommy Williams Homes, Gainesville, Florida

    Office of Energy Efficiency and Renewable Energy (EERE)

    Building America research has shown that high-performance homes can potentially give builders an edge in the marketplace and can boost sales, but it doesn't happen automatically. It requires a tailored, easy-to-understand marketing campaign, and sometimes a little flair. This case study highlights the successful marketing approach of Tommy Williams Homes, which devotes resources to advertising, targeted social media outlets and blogs, realtor education seminars, and groundbreaking and open house celebrations. As a result, in one community, 2013 property sales records show that TWH outsells the only other builder in the development at a higher price, with fewer days on the market.

  17. ALCF Early Science Program Tim Williams (ESP Manager) HPC User Forum

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Early Science Program Tim Williams (ESP Manager) HPC User Forum April 15, 2015 Argonne Leadership Computing Facility 2 ¤ Mission: capability computing (leadership-class) INCITE ALCC Director's D iscre2onary Company University Govt. L ab Foreign USA DOE NSF NIST Company Research F unding S ource ... Production Systems (ALCF-2) 3 Mira - IBM Blue Gene/Q system ¥ 49,152 nodes / 786,432 cores ¥ PowerPC A2 cpu - 16 cores, 4 HW threads/core ¥ 786 TB of memory ¥ Peak flop rate: 10 PF

  18. Prince William Sound disabled tanker towing study. Part 1. Evaluation of existing equipment, personnel and procedures

    SciTech Connect

    Not Available

    1993-08-01

    The study has been undertaken by the Glosten Associates, Inc., to evaluate the existing capability for emergency towing at Prince William Sound and to examine alternatives that could enhance the escort and assist capabilities for disabled tankers within the waterway from the Alyeska Oil Terminal at the Port of Valdez to the Gulf of Alaska outside Hinchinbrook Entrance. Part 1, reported herein, is an objective evaluation by an experienced salvage towing master of the existing tugs, emergency towing equipment, towing practices, and discussion of alternative tug types.

  19. New Whole-House Solutions Case Study: William Ryan Homes, Tampa, Florida

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Changes in the Florida Building Code and a company-wide "green" initiative launched in the fall of 2008 gave William Ryan Homes' Tampa Division the push it needed to implement energy-efficient measures as standard practice in all of its new homes. Building America's Consortium for Advanced Residential Buildings (CARB) analyzed nine new house designs by the builder and found all of the designs would achieve home energy rating (HERS) scores of 65 to 70. The homes also meet the

  20. WILLIAM C. LOUIS Los Alamos National Laboratory M.S. H846 Los

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    WILLIAM C. LOUIS Los Alamos National Laboratory M.S. H846 Los Alamos, NM 87545 louis@lanl.gov, 505/667-6723 EMPLOYMENT Technical Staff Member, Los Alamos National Laboratory, P-Division, 1987-present Assistant Professor, Princeton University, 1981-1987 Research Associate, Rutherford Laboratory, 1978-1981 POSITIONS LANL Program Manager for Nuclear Physics, 2004-2009 Co-Spokesperson of the BooNE Neutrino Experiment at Fermilab, 1998-2007 Spokesperson of the LSND Neutrino Experiment at Los Alamos,

  1. West Windsor-Plainsboro South High School & William Annin Middle School win

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Virginia N.J. Regional Science Bowl at PPPL | Princeton Plasma Physics Lab

    West Windsor-Plainsboro South High School & William Annin Middle School win N.J. Regional Science Bowl at PPPL Top science whizzes will go to national contest in Washington, D.C. By Jeanne Jackson DeVoe February 23, 2016 Tweet Widget Google Plus One Share on Facebook The West Windsor-Plainsboro South High School team buzzes in an answer as they compete against Millburn High School in Round 12 of the New Jersey

  2. Business Solutions Case Study: Marketing Zero Energy Homes: Tommy Williams Homes, Gainesville, Florida

    SciTech Connect

    2015-06-01

    Building America research has shown that high-performance homes can potentially give builders an edge in the marketplace and can boost sales, but it doesn't happen automatically. It requires a tailored, easy-to-understand marketing campaign, and sometimes a little flair. This case study highlights the successful marketing approach of Tommy Williams Homes, which devotes resources to advertising, targeted social media outlets and blogs, realtor education seminars, and groundbreaking and open house celebrations. As a result, in one community, 2013 property sales records show that TWH outsells the only other builder in the development at a higher price, with fewer days on the market.

  3. Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

    SciTech Connect

    Zhang, J.; Hodge, B. M.; Florita, A.; Lu, S.; Hamann, H. F.; Banunarayanan, V.

    2013-10-01

    Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The results show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.

  4. Wind speed forecasting in the central California wind resource area

    SciTech Connect

    McCarthy, E.F.

    1997-12-31

    A wind speed forecasting program was implemented in the summer seasons of 1985 - 87 in the Central California Wind Resource Area (WRA). The forecasting program is designed to use either meteorological observations from the WRA and local upper air observations or upper air observations alone to predict the daily average windspeed at two locations. Forecasts are made each morning at 6 AM and are valid for a 24 hour period. Ease of use is a hallmark of the program as the daily forecast can be made using data entered into a programmable HP calculator. The forecasting program was the first step in a process to examine whether the electrical energy output of an entire wind power generation facility or defined subsections of the same facility could be predicted up to 24 hours in advance. Analysis of the results of the summer season program using standard forecast verification techniques show the program has skill over persistence and climatology.

  5. The impact of forecasted energy price increases on low-income consumers

    SciTech Connect

    Eisenberg, Joel F.

    2005-10-31

    The Department of Energy’s Energy Information Administration (EIA) recently released its short term forecast for residential energy prices for the winter of 2005-2006. The forecast indicates significant increases in fuel costs, particularly for natural gas, propane, and home heating oil, for the year ahead. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation’s low-income households by primary heating fuel type, nationally and by Census Region. The statistics are intended for the use of policymakers in the Department of Energy’s Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2006 fiscal year.

  6. Waste generation forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1995-FY 2002, September 1994 revision

    SciTech Connect

    Not Available

    1994-12-01

    A comprehensive waste-forecasting task was initiated in FY 1991 to provide a consistent, documented estimate of the volumes of waste expected to be generated as a result of U.S. Department of Energy-Oak Ridge Operations (DOE-ORO) Environmental Restoration (ER) OR-1 Project activities. Continual changes in the scope and schedules for remedial action (RA) and decontamination and decommissioning (D&D) activities have required that an integrated data base system be developed that can be easily revised to keep pace with changes and provide appropriate tabular and graphical output. The output can then be analyzed and used to drive planning assumptions for treatment, storage, and disposal (TSD) facilities. The results of this forecasting effort and a description of the data base developed to support it are provided herein. The initial waste-generation forecast results were compiled in November 1991. Since the initial forecast report, the forecast data have been revised annually. This report reflects revisions as of September 1994.

  7. Solar Forecast Improvement Project | Department of Energy

    Energy Saver

    Energy Systems Integration » Solar Energy Grid Integration Systems-Advanced Concepts Solar Energy Grid Integration Systems-Advanced Concepts On September 1, 2011, DOE announced $25.9 million to fund eight solar projects that are targeting ways to develop power electronics and build smarter, more interactive systems and components so that solar energy can be integrated into the electric power distribution and transmission grid at higher levels. Part of the SunShot Systems Integration

  8. Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory

    Office of Scientific and Technical Information (OSTI)

    (BNL) Field Campaign Report (Technical Report) | SciTech Connect Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report Citation Details In-Document Search Title: Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report The Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) [http://www.arm.gov/campaigns/osc2013rwpcf] campaign was scheduled to take place from 15 July

  9. Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory

    Office of Scientific and Technical Information (OSTI)

    (BNL) Field Campaign Report (Technical Report) | SciTech Connect Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report Citation Details In-Document Search Title: Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) Field Campaign Report The Radar Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory (BNL) [http://www.arm.gov/campaigns/osc2013rwpcf] campaign was scheduled to take place from 15 July

  10. Funding Opportunity Announcement for Wind Forecasting Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    in Complex Terrain | Department of Energy Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain April 4, 2014 - 9:47am Addthis On April 4, 2014 the U.S. Department of Energy announced a $2.5 million funding opportunity entitled "Wind Forecasting Improvement Project in Complex Terrain." By researching the physical processes that take place in complex

  11. Wind Forecast Improvement Project Southern Study Area Final Report |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report.pdf (15.76 MB) More Documents & Publications QER - Comment of Edison Electric Institute (EEI) 1 QER - Comment of Canadian Hydropower Association Team roster: Dan Paikowsky, Management; Christian Bain, Entrepreneurship; Noah Meunier, Mechanical Engineering &

  12. Module 6 - Metrics, Performance Measurements and Forecasting | Department

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    of Energy 6 - Metrics, Performance Measurements and Forecasting Module 6 - Metrics, Performance Measurements and Forecasting This module focuses on the metrics and performance measurement tools used in Earned Value. This module reviews metrics such as cost and schedule variance along with cost and schedule performance indices. In addition, this module will outline forecasting tools such as estimate to complete (ETC) and estimate at completion (EAC). Begin Module >> (471

  13. DOE Benefits Forecasts: Report of the External Peer Review Panel |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Benefits Forecasts: Report of the External Peer Review Panel DOE Benefits Forecasts: Report of the External Peer Review Panel A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts. Report of the External Peer Review Panel (777.84 KB) More Documents & Publications Industrial Technologies Funding Profile by Subprogram Survey of Emissions Models for Distributed Combined Heat and Power

  14. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Complex Terrain | Department of Energy Wind Forecasting Improvement Project in Complex Terrain Upcoming Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain February 12, 2014 - 10:47am Addthis On February 11, 2014 the Wind Program announced a Notice of Intent to issue a funding opportunity entitled "Wind Forecasting Improvement Project in Complex Terrain." By researching the physical processes that take place in complex terrain, this funding would improve

  15. Validation of Global Weather Forecast and Climate Models Over...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Validation of Global Weather Forecast and Climate Models Over the North Slope of Alaska Xie, Shaocheng Lawrence Livermore National Laboratory Klein, Stephen Lawrence Livermore ...

  16. DOE Publishes New Forecast of Energy Savings from LED Lighting...

    Office of Environmental Management (EM)

    Addthis Related Articles DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting DOE Publishes Pricing and Efficacy Trend Analysis for Utility Program ...

  17. Wind Power Forecasting Error Distributions: An International Comparison; Preprint

    SciTech Connect

    Hodge, B. M.; Lew, D.; Milligan, M.; Holttinen, H.; Sillanpaa, S.; Gomez-Lazaro, E.; Scharff, R.; Soder, L.; Larsen, X. G.; Giebel, G.; Flynn, D.; Dobschinski, J.

    2012-09-01

    Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

  18. NREL: Resource Assessment and Forecasting - Data and Resources

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Data and Resources National Solar Radiation Database NREL resource assessment and forecasting research information is available from the following sources. Renewable Resource Data ...

  19. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

    SciTech Connect

    Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad

    2015-12-08

    Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

  20. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis

    SciTech Connect

    Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad

    2015-10-02

    Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

  1. DOE Announces Webinars on Solar Forecasting Metrics, the DOE...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    DOE Announces Webinars on Solar Forecasting Metrics, the DOE ... from adopting the latest energy efficiency and renewable ... to liquids technology, advantages of using natural gas, ...

  2. Radar Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    forecasts for solar-energy applications and 2) to provide vertical profiling capabilities for the study of dynamics (i.e., vertical velocity) and hydrometeors in winter storms. ...

  3. FY 2004 Second Quarter Review Forecast of Generation Accumulated...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Bonneville Power Administration Power Business Line Generation (PBL) Accumulated Net Revenue Forecast for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net...

  4. PBL FY 2003 Third Quarter Review Forecast of Generation Accumulated...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    2003 Bonneville Power Administration Power Business Line Generation Accumulated Net Revenue Forecast for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net...

  5. Improving the Accuracy of Solar Forecasting Funding Opportunity...

    Energy Saver

    Through the Improving the Accuracy of Solar Forecasting Funding Opportunity, DOE is funding solar projects that are helping utilities, grid operators, solar power plant owners, and ...

  6. Selected papers on fuel forecasting and analysis

    SciTech Connect

    Gordon, R.L.; Prast, W.G.

    1983-05-01

    Of the 19 presentations at this seminar, covering coal, uranium, oil, and gas issues as well as related EPRI research projects, eleven papers are published in this volume. Nine of the papers primarily address coal-market analysis, coal transportation, and uranium supply. Two additional papers provide an evaluation and perspective on the art and use of coal-supply forecasting models and on the relationship between coal and oil prices. The authors are energy analysts and EPRI research contractors from academia, the consulting profession, and the coal industry. A separate abstract was prepared for each of the 11 papers.

  7. Voluntary Green Power Market Forecast through 2015

    SciTech Connect

    Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

    2010-05-01

    Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

  8. Systems Integration | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Systems Integration Systems Integration Solar and Wind Could Provide up to 30% of Electricity on Eastern Power Grid Solar and Wind Could Provide up to 30% of Electricity on Eastern Power Grid Read more Hawaii DREAMS of New Solar Technologies Hawaii DREAMS of New Solar Technologies Read more Plug and Play Solar PV for American Homes Plug and Play Solar PV for American Homes Read more Watt-Sun: A Multi-Scale, Multi-Modal, Machine-Learning Solar Forecasting Technology Watt-Sun: A Multi-Scale,

  9. Technical analysis in short-term uranium price forecasting

    SciTech Connect

    Schramm, D.S.

    1990-03-01

    As market participants anticipate the end of the current uranium price decline and its subsequent reversal, increased attention will be focused upon forecasting future price movements. Although uranium is economically similar to other mineral commodities, it is questionable whether methodologies used to forecast price movements of such commodities may be successfully applied to uranium.

  10. Hanford Site waste treatment/storage/disposal integration

    SciTech Connect

    MCDONALD, K.M.

    1999-02-24

    In 1998 Waste Management Federal Services of Hanford, Inc. began the integration of all low-level waste, mixed waste, and TRU waste-generating activities across the Hanford site. With seven contractors, dozens of generating units, and hundreds of waste streams, integration was necessary to provide acute waste forecasting and planning for future treatment activities. This integration effort provides disposition maps that account for waste from generation, through processing, treatment and final waste disposal. The integration effort covers generating facilities from the present through the life-cycle, including transition and deactivation. The effort is patterned after the very successful DOE Complex EM Integration effort. Although still in the preliminary stages, the comprehensive onsite integration effort has already reaped benefits. These include identifying significant waste streams that had not been forecast, identifying opportunities for consolidating activities and services to accelerate schedule or save money; and identifying waste streams which currently have no path forward in the planning baseline. Consolidation/integration of planned activities may also provide opportunities for pollution prevention and/or avoidance of secondary waste generation. A workshop was held to review the waste disposition maps, and to identify opportunities with potential cost or schedule savings. Another workshop may be held to follow up on some of the long-term integration opportunities. A change to the Hanford waste forecast data call would help to align the Solid Waste Forecast with the new disposition maps.

  11. NREL: Transmission Grid Integration - Hawaii Solar Integration...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Wholesale Electricity Market Operations Energy Imbalance Markets FESTIV Model Active Power Controls Generator Modeling Forecasting Grid Simulation Transmission Planning & Analysis

  12. The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations | Department of Energy The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The Wind Forecast Improvement

  13. Comparison of Wind Power and Load Forecasting Error Distributions: Preprint

    SciTech Connect

    Hodge, B. M.; Florita, A.; Orwig, K.; Lew, D.; Milligan, M.

    2012-07-01

    The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent System Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.

  14. Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

    DOE PAGES [OSTI]

    Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

    2015-02-14

    Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equationsmore » at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.« less

  15. Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

    SciTech Connect

    Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

    2015-02-14

    Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equations at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.

  16. Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy

    SciTech Connect

    Parks, K.; Wan, Y. H.; Wiener, G.; Liu, Y.

    2011-10-01

    higher. In organized electricity markets, units that are committed for reliability reasons are paid their offer price even when prevailing market prices are lower. Often, these uplift charges are allocated to market participants that caused the inefficient dispatch in the first place. Thus, wind energy facilities are burdened with their share of costs proportional to their forecast errors. For Xcel Energy, wind energy uncertainty costs manifest depending on specific market structures. In the Public Service of Colorado (PSCo), inefficient commitment and dispatch caused by wind uncertainty increases fuel costs. Wind resources participating in the Midwest Independent System Operator (MISO) footprint make substantial payments in the real-time markets to true-up their day-ahead positions and are additionally burdened with deviation charges called a Revenue Sufficiency Guarantee (RSG) to cover out of market costs associated with operations. Southwest Public Service (SPS) wind plants cause both commitment inefficiencies and are charged Southwest Power Pool (SPP) imbalance payments due to wind uncertainty and variability. Wind energy forecasting helps mitigate these costs. Wind integration studies for the PSCo and Northern States Power (NSP) operating companies have projected increasing costs as more wind is installed on the system due to forecast error. It follows that reducing forecast error would reduce these costs. This is echoed by large scale studies in neighboring regions and states that have recommended adoption of state-of-the-art wind forecasting tools in day-ahead and real-time planning and operations. Further, Xcel Energy concluded reduction of the normalized mean absolute error by one percent would have reduced costs in 2008 by over $1 million annually in PSCo alone. The value of reducing forecast error prompted Xcel Energy to make substantial investments in wind energy forecasting research and development.

  17. 3TIER Environmental Forecast Group Inc 3TIER | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    TIER Environmental Forecast Group Inc 3TIER Jump to: navigation, search Name: 3TIER Environmental Forecast Group Inc (3TIER) Place: Seattle, Washington Zip: 98121 Sector: Renewable...

  18. Short-Term Energy Outlook Model Documentation: Macro Bridge Procedure to Update Regional Macroeconomic Forecasts with National Macroeconomic Forecasts

    Reports and Publications

    2010-01-01

    The Regional Short-Term Energy Model (RSTEM) uses macroeconomic variables such as income, employment, industrial production and consumer prices at both the national and regional1 levels as explanatory variables in the generation of the Short-Term Energy Outlook (STEO). This documentation explains how national macroeconomic forecasts are used to update regional macroeconomic forecasts through the RSTEM Macro Bridge procedure.

  19. Incorporating Uncertainty of Wind Power Generation Forecast into Power System Operation, Dispatch, and Unit Commitment Procedures

    SciTech Connect

    Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian; Huang, Zhenyu; Subbarao, Krishnappa

    2011-06-23

    An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. An assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty - both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures). A new method called the 'flying-brick' technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through EMS integration illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems in control rooms.

  20. Incorporating Wind Generation Forecast Uncertainty into Power System Operation, Dispatch, and Unit Commitment Procedures

    SciTech Connect

    Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Subbarao, Krishnappa

    2010-10-19

    In this paper, an approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the "flying-brick" technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through integration with an EMS system illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems from other vendors.

  1. Incorporating Forecast Uncertainty in Utility Control Center

    SciTech Connect

    Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian

    2014-07-09

    Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)

  2. Forecasting of municipal solid waste quantity in a developing country using multivariate grey models

    SciTech Connect

    Intharathirat, Rotchana; Abdul Salam, P.; Kumar, S.; Untong, Akarapong

    2015-05-15

    Highlights: • Grey model can be used to forecast MSW quantity accurately with the limited data. • Prediction interval overcomes the uncertainty of MSW forecast effectively. • A multivariate model gives accuracy associated with factors affecting MSW quantity. • Population, urbanization, employment and household size play role for MSW quantity. - Abstract: In order to plan, manage and use municipal solid waste (MSW) in a sustainable way, accurate forecasting of MSW generation and composition plays a key role. It is difficult to carry out the reliable estimates using the existing models due to the limited data available in the developing countries. This study aims to forecast MSW collected in Thailand with prediction interval in long term period by using the optimized multivariate grey model which is the mathematical approach. For multivariate models, the representative factors of residential and commercial sectors affecting waste collected are identified, classified and quantified based on statistics and mathematics of grey system theory. Results show that GMC (1, 5), the grey model with convolution integral, is the most accurate with the least error of 1.16% MAPE. MSW collected would increase 1.40% per year from 43,435–44,994 tonnes per day in 2013 to 55,177–56,735 tonnes per day in 2030. This model also illustrates that population density is the most important factor affecting MSW collected, followed by urbanization, proportion employment and household size, respectively. These mean that the representative factors of commercial sector may affect more MSW collected than that of residential sector. Results can help decision makers to develop the measures and policies of waste management in long term period.

  3. Overview and Meteorological Validation of the Wind Integration National Dataset toolkit

    SciTech Connect

    Draxl, C.; Hodge, B. M.; Clifton, A.; McCaa, J.

    2015-04-13

    The Wind Integration National Dataset (WIND) Toolkit described in this report fulfills these requirements, and constitutes a state-of-the-art national wind resource data set covering the contiguous United States from 2007 to 2013 for use in a variety of next-generation wind integration analyses and wind power planning. The toolkit is a wind resource data set, wind forecast data set, and wind power production and forecast data set derived from the Weather Research and Forecasting (WRF) numerical weather prediction model. WIND Toolkit data are available online for over 116,000 land-based and 10,000 offshore sites representing existing and potential wind facilities.

  4. Development and testing of improved statistical wind power forecasting methods.

    SciTech Connect

    Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J.

    2011-12-06

    Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios

  5. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema

    Gonzalez, Frank

    2016-07-12

    After a review of tsunami statistics and the destruction caused by tsunamis, a means of forecasting tsunamis is discussed as part of an overall program of reducing fatalities through hazard assessment, education, training, mitigation, and a tsunami warning system. The forecast is accomplished via a concept called Deep Ocean Assessment and Reporting of Tsunamis (DART). Small changes of pressure at the sea floor are measured and relayed to warning centers. Under development is an international modeling network to transfer, maintain, and improve tsunami forecast models.

  6. Wind Energy Technology Trends: Comparing and Contrasting Recent Cost and Performance Forecasts (Poster)

    SciTech Connect

    Lantz, E.; Hand, M.

    2010-05-01

    Poster depicts wind energy technology trends, comparing and contrasting recent cost and performance forecasts.

  7. Development and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices

    Energy.gov [DOE]

    Development and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices

  8. Solar Trackers Market Forecast | OpenEI Community

    OpenEI (Open Energy Information) [EERE & EIA]

    Solar Trackers Market Forecast Home John55364's picture Submitted by John55364(100) Contributor 12 May, 2015 - 03:54 Solar Trackers Market - Global Industry Analysis, Size, Share,...

  9. Energy Forecasting Framework and Emissions Consensus Tool (EFFECT...

    OpenEI (Open Energy Information) [EERE & EIA]

    Tool (EFFECT) EFFECT is an open, Excel-based modeling tool used to forecast greenhouse gas emissions from a range of development scenarios at the regional and national levels....

  10. Value of Improved Short-Term Wind Power Forecasting

    SciTech Connect

    Hodge, B. M.; Florita, A.; Sharp, J.; Margulis, M.; Mcreavy, D.

    2015-02-01

    This report summarizes an assessment of improved short-term wind power forecasting in the California Independent System Operator (CAISO) market and provides a quantification of its potential value.

  11. Recently released EIA report presents international forecasting data

    SciTech Connect

    1995-05-01

    This report presents information from the Energy Information Administration (EIA). Articles are included on international energy forecasting data, data on the use of home appliances, gasoline prices, household energy use, and EIA information products and dissemination avenues.

  12. DOE Releases Latest Report on Energy Savings Forecast of Solid...

    Energy.gov [DOE] (indexed site)

    The sixth iteration of the Energy Savings Forecast of Solid-State Lighting in General Illumination Applications compares the annual lighting energy consumption in the U.S. with and ...

  13. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect

    Yoo, Wucherl; Sim, Alex

    2014-07-07

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  14. The Wind Forecast Improvement Project (WFIP): A Public/Private...

    Energy.gov [DOE] (indexed site)

    The Wind Forecast Improvement Project (WFIP) is a U. S. Department of Energy (DOE) sponsored research project whose overarching goals are to improve the accuracy of short-term wind ...

  15. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    U.S. DEPARTMENT OF HP IENERGY Office of Science DOESC-ARM-15-024 915-MHz Wind Profiler ... M Jensen et al., March 2016, DOESC-ARM-15-024 915-MHz Wind Profiler for Cloud Forecasting ...

  16. PBL FY 2002 Second Quarter Review Forecast of Generation Accumulated...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Slice true-ups, and actual expense levels. Any variation of these can change the net revenue situation. FY 2002 Forecasted Second Quarter Results 170 (418) FY 2002 Unaudited...

  17. Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels

    Reports and Publications

    2003-01-01

    This paper presents a short-term monthly forecasting model of West Texas Intermediate crude oil spot price using Organization for Economic Cooperation and Development (OECD) petroleum inventory levels.

  18. Expert Panel: Forecast Future Demand for Medical Isotopes | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy Expert Panel: Forecast Future Demand for Medical Isotopes Expert Panel: Forecast Future Demand for Medical Isotopes The Expert Panel has concluded that the Department of Energy and National Institutes of Health must develop the capability to produce a diverse supply of radioisotopes for medical use in quantities sufficient to support research and clinical activities. Such a capability would prevent shortages of isotopes, reduce American dependence on foreign radionuclide sources and

  19. Energy Department Forecasts Geothermal Achievements in 2015 | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy Forecasts Geothermal Achievements in 2015 Energy Department Forecasts Geothermal Achievements in 2015 The 40th annual Stanford Geothermal Workshop in January featured speakers in the geothermal sector, including Jay Nathwani, Acting Director of the Energy Department's Geothermal Technologies Office. Nathwani shared achievements and challenges in the program's technical portfolio. The 40th annual Stanford Geothermal Workshop in January featured speakers in the geothermal sector,

  20. Study forecasts disappearance of conifers due to climate change

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Study forecasts disappearance of conifers due to climate change Study forecasts disappearance of conifers due to climate change New results, reported in a paper released today in the journal Nature Climate Change, suggest that global models may underestimate predictions of forest death. December 21, 2015 Los Alamos scientist Nate McDowell discusses how climate change is killing trees with PBS NewsHour reporter Miles O'Brien. Los Alamos scientist Nate McDowell discusses how climate change is

  1. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National

    Office of Scientific and Technical Information (OSTI)

    Laboratory (Technical Report) | SciTech Connect 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory Citation Details In-Document Search Title: 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory When considering the amount of shortwave radiation incident on a photovoltaic solar array and, therefore, the amount and stability of the energy output from the system, clouds represent the greatest source of short-term (i.e., scale of minutes to

  2. Project Profile: Forecasting and Influencing Technological Progress in

    Energy Saver

    Solar Energy | Department of Energy Soft Costs » Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Logos of the University of North Carolina at Charlotte, Arizona State University, and the University of Oxford. -- This project is inactive -- The University of North Carolina at Charlotte, along with their partners at Arizona State University and the University of Oxford,

  3. Wind Power Forecasting Error Distributions: An International...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    be presented at The 11th Annual International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power ...

  4. Wind power forecasting : state-of-the-art 2009.

    SciTech Connect

    Monteiro, C.; Bessa, R.; Miranda, V.; Botterud, A.; Wang, J.; Conzelmann, G.; Decision and Information Sciences; INESC Porto

    2009-11-20

    Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and

  5. Weather-based forecasts of California crop yields

    SciTech Connect

    Lobell, D B; Cahill, K N; Field, C B

    2005-09-26

    Crop yield forecasts provide useful information to a range of users. Yields for several crops in California are currently forecast based on field surveys and farmer interviews, while for many crops official forecasts do not exist. As broad-scale crop yields are largely dependent on weather, measurements from existing meteorological stations have the potential to provide a reliable, timely, and cost-effective means to anticipate crop yields. We developed weather-based models of state-wide yields for 12 major California crops (wine grapes, lettuce, almonds, strawberries, table grapes, hay, oranges, cotton, tomatoes, walnuts, avocados, and pistachios), and tested their accuracy using cross-validation over the 1980-2003 period. Many crops were forecast with high accuracy, as judged by the percent of yield variation explained by the forecast, the number of yields with correctly predicted direction of yield change, or the number of yields with correctly predicted extreme yields. The most successfully modeled crop was almonds, with 81% of yield variance captured by the forecast. Predictions for most crops relied on weather measurements well before harvest time, allowing for lead times that were longer than existing procedures in many cases.

  6. Updated Eastern Interconnect Wind Power Output and Forecasts for ERGIS: July 2012

    SciTech Connect

    Pennock, K.

    2012-10-01

    AWS Truepower, LLC (AWST) was retained by the National Renewable Energy Laboratory (NREL) to update wind resource, plant output, and wind power forecasts originally produced by the Eastern Wind Integration and Transmission Study (EWITS). The new data set was to incorporate AWST's updated 200-m wind speed map, additional tall towers that were not included in the original study, and new turbine power curves. Additionally, a primary objective of this new study was to employ new data synthesis techniques developed for the PJM Renewable Integration Study (PRIS) to eliminate diurnal discontinuities resulting from the assimilation of observations into mesoscale model runs. The updated data set covers the same geographic area, 10-minute time resolution, and 2004?2006 study period for the same onshore and offshore (Great Lakes and Atlantic coast) sites as the original EWITS data set.

  7. Principal Deputy Chief William A. Eckroade's Written Testimony Before the Subcommittee on Financial and Contracting Oversight Committee on Homeland Security and Governmental Affairs (March 11, 2014)

    Energy.gov [DOE]

    Written statement of  William A. Eckroade's Written Testimony Before the Subcommittee on Financial and Contracting Oversight Committee on Homeland Security and Governmental Affairs on March 11,...

  8. The Prince William Sound herring fishery following the Exxon Valdez oil spill of 1989

    SciTech Connect

    Hose, J.E.; Brown, E.; Marty, G.D.; McGurk, M.D.; Norcross, B.L.; Short, J.

    1995-12-31

    The Exxon Valdez oil (EVO) spill of 1989 occurred a few weeks before herring spawned in Prince William Sound (PWS), AK. An estimated 40% to 50% of the egg biomass sustained exposure during early development, and the majority of pelagic larvae were collected within the oil trajectory path. Sublethal effects observed at hatch (morphologic defects and genetic damage) were related to ambient EVO concentrations. Reduced survival rates, decreased growth, genetic damage and histopathological changes were measured in pelagic larvae from oiled areas. However, because the 1989 year class is one of the smallest cohorts now in PWS, population effects are difficult to assess. From 1990 to 1992, population abundance and reproductive potential remained high. When the 1989 year class was fully recruited (1993--1994), the spawning population decreased by 50% to 75% of the expected abundance. Many of the surviving fish were infected with viral hemorrhagic septicemia (VHS) and failed to spawn. Proposed causes for the VHS epizootic include previous oil exposure, density-dependent effects following the 1989 fishery closure, and reduced food availability from 1990 to 1994.

  9. Standardized Software for Wind Load Forecast Error Analyses and Predictions Based on Wavelet-ARIMA Models - Applications at Multiple Geographically Distributed Wind Farms

    SciTech Connect

    Hou, Zhangshuan; Makarov, Yuri V.; Samaan, Nader A.; Etingov, Pavel V.

    2013-03-19

    Given the multi-scale variability and uncertainty of wind generation and forecast errors, it is a natural choice to use time-frequency representation (TFR) as a view of the corresponding time series represented over both time and frequency. Here we use wavelet transform (WT) to expand the signal in terms of wavelet functions which are localized in both time and frequency. Each WT component is more stationary and has consistent auto-correlation pattern. We combined wavelet analyses with time series forecast approaches such as ARIMA, and tested the approach at three different wind farms located far away from each other. The prediction capability is satisfactory -- the day-ahead prediction of errors match the original error values very well, including the patterns. The observations are well located within the predictive intervals. Integrating our wavelet-ARIMA (stochastic) model with the weather forecast model (deterministic) will improve our ability significantly to predict wind power generation and reduce predictive uncertainty.

  10. A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China

    SciTech Connect

    Xu, Lilai; Gao, Peiqing; Cui, Shenghui; Liu, Chun

    2013-06-15

    Highlights: ► We propose a hybrid model that combines seasonal SARIMA model and grey system theory. ► The model is robust at multiple time scales with the anticipated accuracy. ► At month-scale, the SARIMA model shows good representation for monthly MSW generation. ► At medium-term time scale, grey relational analysis could yield the MSW generation. ► At long-term time scale, GM (1, 1) provides a basic scenario of MSW generation. - Abstract: Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 – 1.5 times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 – 2.5 times the value for 2010. The hybrid model proposed in this paper can enable decision makers to

  11. Interpolating Low Time-Resolution Forecast Data

    Energy Science and Technology Software Center

    2015-11-03

    Methodology that interpolates low time-resolution data (e.g., hourly) to high time-resolution (e.g., minutely) with variability patterns extracted from historical records. Magnitude of the variability inserted into the low timeresolution data can be adjusted according to the installed capacity represented by the low time-resolution data compared to that by historical records. This approach enables detailed analysis of the impacts from wind and solar on power system intra-hour operations and balancing reserve requirements even with only hourlymore » data. It also allows convenient creation of high resolution wind or solar generation data with various degree of variability to investigate their operational impacts. The methodology comprises of the following steps: 1. Smooth the historical data (set A) with an appropriate window length l to get its trend (set B); l can be a fraction of an hour (e.g., 15 minutes) or longer than an hour, of which the length of the variability patterns will be; 2. Extract the variable component (set C) of historical data by subtracting the smooth trend from it, i.e. set C = set A – set B 3. For each window length l of the variable component data set, find the average value x (will call it base component) of the corresponding window of the historical data set; 4. Define a series of segments (set D) that the values of data will be grouped into, e.g. (0, 0.1), (0.1, 0.2), …, (0.9, 1.0) after normalization; Link each variability pattern to a data segment based on its corresponding base component x; after this step, each data segment should be linked to multiple variability patterns after this step; 5. Use spline function to interpolate the low time-resolution forecast data (set E) to become a high time-resolution smooth curve (set F); 6. Based on the window length l , calculate the average value y in each window length of set F; find the data segment that y belongs to; then randomly select one of the variability patterns linked to this

  12. Forecasting the 2013–2014 influenza season using Wikipedia

    DOE PAGES [OSTI]

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are appliedmore » to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.« less

  13. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are applied to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.

  14. Survey of Variable Generation Forecasting in the West: August 2011 - June 2012

    SciTech Connect

    Porter, K.; Rogers, J.

    2012-04-01

    This report surveyed Western Interconnection Balancing Authorities regarding their implementation of variable generation forecasting, the lessons learned to date, and recommendations they would offer to other Balancing Authorities who are considering variable generation forecasting. Our survey found that variable generation forecasting is at an early implementation stage in the West. Eight of the eleven Balancing Authorities interviewed began forecasting in 2008 or later. It also appears that less than one-half of the Balancing Authorities in the West are currently utilizing variable generation forecasting, suggesting that more Balancing Authorities in the West will engage in variable generation forecasting should more variable generation capacity be added.

  15. Grid Integration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Centers Grid Integration HomeTag:Grid Integration Matt ... Research & Capabilities, Solar Sandia Labs Presents Grid ... Engineers convenes the Power Energy Society to address ...

  16. Grid Integration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Grid Integration HomeGrid Integration epri-presentations-av... and the Electric Power Research Institute (EPRI) ... Events, Renewable Energy, Solar Newsletter|Comments Off on ...

  17. A Scenario Generation Method for Wind Power Ramp Events Forecasting

    SciTech Connect

    Cui, Ming-Jian; Ke, De-Ping; Sun, Yuan-Zhang; Gan, Di; Zhang, Jie; Hodge, Bri-Mathias

    2015-07-03

    Wind power ramp events (WPREs) have received increasing attention in recent years due to their significant impact on the reliability of power grid operations. In this paper, a novel WPRE forecasting method is proposed which is able to estimate the probability distributions of three important properties of the WPREs. To do so, a neural network (NN) is first proposed to model the wind power generation (WPG) as a stochastic process so that a number of scenarios of the future WPG can be generated (or predicted). Each possible scenario of the future WPG generated in this manner contains the ramping information, and the distributions of the designated WPRE properties can be stochastically derived based on the possible scenarios. Actual data from a wind power plant in the Bonneville Power Administration (BPA) was selected for testing the proposed ramp forecasting method. Results showed that the proposed method effectively forecasted the probability of ramp events.

  18. 1980 annual report to Congress: Volume three, Forecasts: Summary

    SciTech Connect

    Not Available

    1981-05-27

    This report presents an overview of forecasts of domestic energy consumption, production, and prices for the year 1990. These results are selected from more detailed projections prepared and published in Volume 3 of the Energy Information Administration 1980 Annual Report to Congress. This report focuses specifically upon the 1980's and concentrates upon similarities and differences in the domestic energy system, as forecast, compared to the national experience in the years immediately following the 1973--1974 oil embargo. Interest in the 1980's stems not only from its immediacy in time, but also from its importance as a time in which certain adjustments to higher energy prices are expected to take place. The forecasts presented do not attempt to account for all of this wide range of potentially important forces that could conceivably alter the energy situation. Instead, the projections are based on a particular set of assumptions that seems reasonable in light of what is currently known. 9 figs., 25 tabs.

  19. Lessons from Large-Scale Renewable Energy Integration Studies: Preprint

    SciTech Connect

    Bird, L.; Milligan, M.

    2012-06-01

    In general, large-scale integration studies in Europe and the United States find that high penetrations of renewable generation are technically feasible with operational changes and increased access to transmission. This paper describes other key findings such as the need for fast markets, large balancing areas, system flexibility, and the use of advanced forecasting.

  20. CCPP-ARM Parameterization Testbed Model Forecast Data

    DOE Data Explorer

    Klein, Stephen

    Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

  1. Forecast of contracting and subcontracting opportunities. Fiscal year 1996

    SciTech Connect

    1996-02-01

    This forecast of prime and subcontracting opportunities with the U.S. Department of Energy and its MAO contractors and environmental restoration and waste management contractors, is the Department`s best estimate of small, small disadvantaged and women-owned small business procurement opportunities for fiscal year 1996. The information contained in the forecast is published in accordance with Public Law 100-656. It is not an invitation for bids, a request for proposals, or a commitment by DOE to purchase products or services. Each procurement opportunity is based on the best information available at the time of publication and may be revised or cancelled.

  2. Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Wind Energy Predictable: New Profilers Provide Hourly Forecasts Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts May 11, 2016 - 6:48pm Addthis Balancing the power grid is an art-or at least a scientific study in chaos-and the Energy Department is hoping wind energy can take a greater role in the act. Yet, the intermittency of wind-sometimes it's blowing, sometimes it's not-makes adding it smoothly to the nation's electrical grid a challenge. If wind

  3. CCPP-ARM Parameterization Testbed Model Forecast Data

    DOE Data Explorer

    Klein, Stephen

    2008-01-15

    Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

  4. Are there Gains from Pooling Real-Time Oil Price Forecasts?

    Energy Information Administration (EIA) (indexed site)

    ... Gamma and that of Q is inverse Wishart. 5 Our forecasts take into account that the model parameters continue to drift over the forecast horizon according to their law of motion. ...

  5. Impacts of Improved Day-Ahead Wind Forecasts on Power Grid Operations: September 2011

    SciTech Connect

    Piwko, R.; Jordan, G.

    2011-11-01

    This study analyzed the potential benefits of improving the accuracy (reducing the error) of day-ahead wind forecasts on power system operations, assuming that wind forecasts were used for day ahead security constrained unit commitment.

  6. Status of Centralized Wind Power Forecasting in North America: May 2009-May 2010

    SciTech Connect

    Porter, K.; Rogers, J.

    2010-04-01

    Report surveys grid wind power forecasts for all wind generators, which are administered by utilities or regional transmission organizations (RTOs), typically with the assistance of one or more wind power forecasting companies.

  7. DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting

    Energy.gov [DOE]

    DOE has published a new report forecasting the energy savings of LED white-light sources compared with conventional white-light sources. The sixth iteration of the Energy Savings Forecast of Solid...

  8. Integrating Variable Renewable Energy: Challenges and Solutions

    SciTech Connect

    Bird, L.; Milligan, M.; Lew, D.

    2013-09-01

    In the U.S., a number of utilities are adopting higher penetrations of renewables, driven in part by state policies. While power systems have been designed to handle the variable nature of loads, the additional supply-side variability and uncertainty can pose new challenges for utilities and system operators. However, a variety of operational and technical solutions exist to help integrate higher penetrations of wind and solar generation. This paper explores renewable energy integration challenges and mitigation strategies that have been implemented in the U.S. and internationally, including forecasting, demand response, flexible generation, larger balancing areas or balancing area cooperation, and operational practices such as fast scheduling and dispatch.

  9. Comprehensive Solutions for Integration of Solar Resources into Grid

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Operations | Department of Energy Comprehensive Solutions for Integration of Solar Resources into Grid Operations Comprehensive Solutions for Integration of Solar Resources into Grid Operations AWS truepower logo.png -- This project is inactive -- This project primarily looks at the benefits from more cost-effective unit commitment and dispatch, and reduction in balancing reserves due to reducing uncertainty in solar forecasting. This project will improve the Pacific Northwest National

  10. Beyond "Partly Sunny": A Better Solar Forecast | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast December 7, 2012 - 10:00am Addthis The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods of cloud coverage. | Photo by Dennis Schroeder/NREL. The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods

  11. Central Wind Power Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities

    SciTech Connect

    Porter, K.; Rogers, J.

    2009-12-01

    The report addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America.

  12. Review of Wind Energy Forecasting Methods for Modeling Ramping Events

    SciTech Connect

    Wharton, S; Lundquist, J K; Marjanovic, N; Williams, J L; Rhodes, M; Chow, T K; Maxwell, R

    2011-03-28

    Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

  13. Weather Research and Forecasting Model with the Immersed Boundary Method

    Energy Science and Technology Software Center

    2012-05-01

    The Weather Research and Forecasting (WRF) Model with the immersed boundary method is an extension of the open-source WRF Model available for wwww.wrf-model.org. The new code modifies the gridding procedure and boundary conditions in the WRF model to improve WRF's ability to simutate the atmosphere in environments with steep terrain and additionally at high-resolutions.

  14. Navy mobility fuels forecasting system report: World petroleum trade forecasts for the year 2000

    SciTech Connect

    Das, S.

    1991-12-01

    The Middle East will continue to play the dominant role of a petroleum supplier in the world oil market in the year 2000, according to business-as-usual forecasts published by the US Department of Energy. However, interesting trade patterns will emerge as a result of the democratization in the Soviet Union and Eastern Europe. US petroleum imports will increase from 46% in 1989 to 49% in 2000. A significantly higher level of US petroleum imports (principally products) will be coming from Japan, the Soviet Union, and Eastern Europe. Several regions, the Far East, Japan, Latin American, and Africa will import more petroleum. Much uncertainty remains about of the level future Soviet crude oil production. USSR net petroleum exports will decrease; however, the United States and Canada will receive some of their imports from the Soviet Union due to changes in the world trade patterns. The Soviet Union can avoid becoming a net petroleum importer as long as it (1) maintains enough crude oil production to meet its own consumption and (2) maintains its existing refining capacities. Eastern Europe will import approximately 50% of its crude oil from the Middle East.

  15. Grid Integration

    SciTech Connect

    Not Available

    2008-09-01

    Summarizes the goals and activities of the DOE Solar Energy Technologies Program efforts within its grid integration subprogram.

  16. Forecasting photovoltaic array power production subject to mismatch losses

    SciTech Connect

    Picault, D.; Raison, B.; Bacha, S.; de la Casa, J.; Aguilera, J.

    2010-07-15

    The development of photovoltaic (PV) energy throughout the world this last decade has brought to light the presence of module mismatch losses in most PV applications. Such power losses, mainly occasioned by partial shading of arrays and differences in PV modules, can be reduced by changing module interconnections of a solar array. This paper presents a novel method to forecast existing PV array production in diverse environmental conditions. In this approach, field measurement data is used to identify module parameters once and for all. The proposed method simulates PV arrays with adaptable module interconnection schemes in order to reduce mismatch losses. The model has been validated by experimental results taken on a 2.2 kW{sub p} plant, with three different interconnection schemes, which show reliable power production forecast precision in both partially shaded and normal operating conditions. Field measurements show interest in using alternative plant configurations in PV systems for decreasing module mismatch losses. (author)

  17. NREL: Energy Analysis - Energy Forecasting and Modeling Staff

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Elizabeth Torres Clayton Barrows Dave Bielen Aaron Bloom Greg Brinkman Brian W Bush Stuart Cohen Wesley Cole Paul Denholm Nicholas DiOrio Aron Dobos Kelly Eurek Janine Freeman Bethany Frew Pieter Gagnon Elaine Hale

  18. Forecast of transportation energy demand through the year 2010

    SciTech Connect

    Mintz, M.M.; Vyas, A.D.

    1991-04-01

    Since 1979, the Center for Transportation Research (CTR) at Argonne National Laboratory (ANL) has produced baseline projections of US transportation activity and energy demand. These projections and the methodologies used to compute them are documented in a series of reports and research papers. As the lastest in this series of projections, this report documents the assumptions, methodologies, and results of the most recent projection -- termed ANL-90N -- and compares those results with other forecasts from the current literature, as well as with the selection of earlier Argonne forecasts. This current forecast may be used as a baseline against which to analyze trends and evaluate existing and proposed energy conservation programs and as an illustration of how the Transportation Energy and Emission Modeling System (TEEMS) works. (TEEMS links disaggregate models to produce an aggregate forecast of transportation activity, energy use, and emissions). This report and the projections it contains were developed for the US Department of Energy's Office of Transportation Technologies (OTT). The projections are not completely comprehensive. Time and modeling effort have been focused on the major energy consumers -- automobiles, trucks, commercial aircraft, rail and waterborne freight carriers, and pipelines. Because buses, rail passengers services, and general aviation consume relatively little energy, they are projected in the aggregate, as other'' modes, and used primarily as scaling factors. These projections are also limited to direct energy consumption. Projections of indirect energy consumption, such as energy consumed in vehicle and equipment manufacturing, infrastructure, fuel refining, etc., were judged outside the scope of this effort. The document is organized into two complementary sections -- one discussing passenger transportation modes, and the other discussing freight transportation modes. 99 refs., 10 figs., 43 tabs.

  19. Assessment of the possibility of forecasting future natural gas curtailments

    SciTech Connect

    Lemont, S.

    1980-01-01

    This study provides a preliminary assessment of the potential for determining probabilities of future natural-gas-supply interruptions by combining long-range weather forecasts and natural-gas supply/demand projections. An illustrative example which measures the probability of occurrence of heating-season natural-gas curtailments for industrial users in the southeastern US is analyzed. Based on the information on existing long-range weather forecasting techniques and natural gas supply/demand projections enumerated above, especially the high uncertainties involved in weather forecasting and the unavailability of adequate, reliable natural-gas projections that take account of seasonal weather variations and uncertainties in the nation's energy-economic system, it must be concluded that there is little possibility, at the present time, of combining the two to yield useful, believable probabilities of heating-season gas curtailments in a form useful for corporate and government decision makers and planners. Possible remedial actions are suggested that might render such data more useful for the desired purpose in the future. The task may simply require the adequate incorporation of uncertainty and seasonal weather trends into modeling systems and the courage to report projected data, so that realistic natural gas supply/demand scenarios and the probabilities of their occurrence will be available to decision makers during a time when such information is greatly needed.

  20. Hydrocarbons in intertidal sediments and mussels from Prince William Sound, Alaska, 1977-1980: Characterization and probable sources. Technical memo

    SciTech Connect

    Karinen, J.F.; Babcock, M.M.; Brown, D.W.; MacLeod, W.D.; Ramos, L.S.

    1993-01-01

    The oil spill that resulted from the March 1989 grounding of the oil tanker vessel Exxon Valdez provides a unique opportunity for the study of marine oil pollution effects because the spilled crude oil polluted a large geographic area that was previously considered pristine. The only sources of confounding hydrocarbons in the areas of Prince William Sound, Alaska, impacted by the spill are naturally occurring hydrocarbons and anthropogenic hydrocarbons from occasional boating activity in the Sound or due to long-range atmospheric transport. The authors' objectives were to determine the levels, intra-annual variability, and interannual variability of selected alkane hydrocarbons and PAHs in intertidal sediments and in M. trossulus tissues at a network of sampling stations over the 4-year sampling period, and if possible to identify the likely sources of hydrocarbons found.

  1. Procurement Integrity

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    - ------------------------------Chapter 3.1 (Dec 2015) 1 Procurement Integrity [Reference: 41 U.S.C. 423, FAR 3.104, DEAR 903.104] Overview This section discusses the requirements of the Procurement Integrity Act and its impact on Federal employees. Background The Department of Energy (DOE), like most federal agencies, purchases many products and services from the private sector. To preserve the integrity of the Federal procurement process and assure fair treatment of bidders, offerors and

  2. Grid Integration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    ... Sandia, DOE Energy Storage Program, GeneSiC Semiconductor, U.S. Army ARDEC: Ultra-High-Voltage Silicon Carbide Thyristors Capabilities, Distribution Grid Integration, Energy, ...

  3. Procurement Integrity

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    To preserve the integrity of the Federal procurement process and assure fair treatment of bidders, offerors and contractors, laws govern the procurement process and the manner in ...

  4. Grid Integration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    CO2 Geothermal Natural Gas Safety, Security & ... Hydrogen Production Market Transformation Fuel Cells ... Google + Vimeo Newsletter Signup SlideShare Grid Integration ...

  5. Insolation integrator

    DOEpatents

    Dougherty, John J.; Rudge, George T.

    1980-01-01

    An electric signal representative of the rate of insolation is integrated to determine if it is adequate for operation of a solar energy collection system.

  6. Two-Way Integration of WRF and CCSM for Regional Climate Simulations

    Office of Scientific and Technical Information (OSTI)

    (Technical Report) | SciTech Connect Two-Way Integration of WRF and CCSM for Regional Climate Simulations Citation Details In-Document Search Title: Two-Way Integration of WRF and CCSM for Regional Climate Simulations Under the support of the DOE award DE-SC0004670, we have successfully developed an integrated climate modeling system by nesting Weather Research and Forecasting (WRF) model within the Community Climate System Model (CCSM) and the ensuing new generation Community Earth System

  7. DE-EE0006329 Integration of Behind-the-Meter PV Fleet Forecasts

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ... The fractional derivatives, which are based on an integro-differential operator, ... Supplied by Itron, ALFS utilizes an artificial neural network methodology that incorporates ...

  8. Value of medium range weather forecasts in the improvement of seasonal hydrologic prediction skill

    SciTech Connect

    Shukla, Shraddhanand; Voisin, Nathalie; Lettenmaier, D. P.

    2012-08-15

    We investigated the contribution of medium range weather forecasts with lead times up to 14 days to seasonal hydrologic prediction skill over the Conterminous United States (CONUS). Three different Ensemble Streamflow Prediction (ESP)-based experiments were performed for the period 1980-2003 using the Variable Infiltration Capacity (VIC) hydrology model to generate forecasts of monthly runoff and soil moisture (SM) at lead-1 (first month of the forecast period) to lead-3. The first experiment (ESP) used a resampling from the retrospective period 1980-2003 and represented full climatological uncertainty for the entire forecast period. In the second and third experiments, the first 14 days of each ESP ensemble member were replaced by either observations (perfect 14-day forecast) or by a deterministic 14-day weather forecast. We used Spearman rank correlations of forecasts and observations as the forecast skill score. We estimated the potential and actual improvement in baseline skill as the difference between the skill of experiments 2 and 3 relative to ESP, respectively. We found that useful runoff and SM forecast skill at lead-1 to -3 months can be obtained by exploiting medium range weather forecast skill in conjunction with the skill derived by the knowledge of initial hydrologic conditions. Potential improvement in baseline skill by using medium range weather forecasts, for runoff (SM) forecasts generally varies from 0 to 0.8 (0 to 0.5) as measured by differences in correlations, with actual improvement generally from 0 to 0.8 of the potential improvement. With some exceptions, most of the improvement in runoff is for lead-1 forecasts, although some improvement in SM was achieved at lead-2.

  9. Central Wind Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities: Revised Edition

    SciTech Connect

    Rogers, J.; Porter, K.

    2011-03-01

    The report and accompanying table addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America. The first part of the table focuses on electric utilities and regional transmission organizations that have central wind power forecasting in place; the second part focuses on electric utilities and regional transmission organizations that plan to adopt central wind power forecasting in 2010. This is an update of the December 2009 report, NREL/SR-550-46763.

  10. Short and Long-Term Perspectives: The Impact on Low-Income Consumers of Forecasted Energy Price Increases in 2008 and A Cap & Trade Carbon Policy in 2030

    SciTech Connect

    Eisenberg, Joel Fred

    2008-01-01

    The Department of Energy's Energy Information Administration (EIA) recently released its short-term forecast for residential energy prices for the winter of 2007-2008. The forecast indicates increases in costs for low-income consumers in the year ahead, particularly for those using fuel oil to heat their homes. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation's low-income households by primary heating fuel type, nationally and by Census Region. The report provides an update of bill estimates provided in a previous study, "The Impact Of Forecasted Energy Price Increases On Low-Income Consumers" (Eisenberg, 2005). The statistics are intended for use by policymakers in the Department of Energy's Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2008 fiscal year. In addition to providing expenditure forecasts for the year immediately ahead, this analysis uses a similar methodology to give policy makers some insight into one of the major policy debates that will impact low-income energy expenditures well into the middle decades of this century and beyond. There is now considerable discussion of employing a cap-and-trade mechanism to first limit and then reduce U.S. emissions of carbon into the atmosphere in order to combat the long-range threat of human-induced climate change. The Energy Information Administration has provided an analysis of projected energy prices in the years 2020 and 2030 for one such cap-and-trade carbon reduction proposal that, when integrated with the RECS 2001 database, provides estimates of how low-income households will be impacted over the long term by such a carbon reduction policy.

  11. ARM - PI Product - CCPP-ARM Parameterization Testbed Model Forecast Data

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    ProductsCCPP-ARM Parameterization Testbed Model Forecast Data ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : CCPP-ARM Parameterization Testbed Model Forecast Data Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are

  12. Report of the external expert peer review panel: DOE benefits forecasts

    SciTech Connect

    None, None

    2006-12-20

    A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts.

  13. Value of Improved Wind Power Forecasting in the Western Interconnection (Poster)

    SciTech Connect

    Hodge, B.

    2013-12-01

    Wind power forecasting is a necessary and important technology for incorporating wind power into the unit commitment and dispatch process. It is expected to become increasingly important with higher renewable energy penetration rates and progress toward the smart grid. There is consensus that wind power forecasting can help utility operations with increasing wind power penetration; however, there is far from a consensus about the economic value of improved forecasts. This work explores the value of improved wind power forecasting in the Western Interconnection of the United States.

  14. Energy Savings Forecast of Solid-State Lighting in General Illuminatio...

    Energy Saver

    (1.54 MB) More Documents & Publications Energy Savings Potential of Solid-State Lighting in General Illumination Applications - Report 2016 SSL Forecast Report LED ADOPTION REPORT

  15. The Value of Improved Wind Power Forecasting in the Western Interconne...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    of this research will facilitate a better functional understanding of wind forecasting accuracy and power system operations at various spatial and temporal scales.* Of particular ...

  16. Review of the Sodium Bearing Waste Treatment Project - Integrated...

    Office of Environmental Management (EM)

    ... Operational Readiness Review OSO Outside Support ... Control SAR Safety Analysis Report SBWTP Sodium Bearing ... Quality Review Board William Eckroade John ...

  17. The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

    SciTech Connect

    Finley, Cathy

    2014-04-30

    This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the

  18. Wind energy and power system operations: a review of wind integration studies to date

    SciTech Connect

    Cesaro, Jennifer de; Porter, Kevin; Milligan, Michael

    2009-12-15

    Wind integration will not be accomplished successfully by doing ''more of the same.'' It will require significant changes in grid planning and operations, continued technical evolution in the design and operation of wind turbines, further adoption and implementation of wind forecasting in the control room, and incorporation of market and policy initiatives to encourage more flexible generation. (author)

  19. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the systems ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  20. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison (Presentation)

    SciTech Connect

    Zhang, J.; Hodge, B.; Miettinen, J.; Holttinen, H.; Gomez-Lozaro, E.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Lovholm, A.; Berge, E.; Dobschinski, J.

    2013-10-01

    This presentation summarizes the work to investigate the uncertainty in wind forecasting at different times of year and compare wind forecast errors in different power systems using large-scale wind power prediction data from six countries: the United States, Finland, Spain, Denmark, Norway, and Germany.

  1. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  2. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    DOE PAGES [OSTI]

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  3. Box Integrals

    SciTech Connect

    Bailey, David H.; Borwein, Jonathan M.; Crandall, Richard E.

    2006-06-01

    By a "box integral" we mean here an expectation $\\langle|\\vec r - \\vec q|^s \\rangle$ where $\\vec r$runs over the unit $n$-cube,with $\\vec q$ and $s$ fixed, explicitly:\\begin eqnarray*&&\\int_01 \\cdots \\int_01 \\left((r_1 - q_1)2 + \\dots+(r_n-q_n)2\\right)^ s/2 \\ dr_1 \\cdots dr_n.\\end eqnarray* The study ofbox integrals leads one naturally into several disparate fields ofanalysis. While previous studies have focused upon symbolic evaluationand asymptotic analysis of special cases (notably $s = 1$), we workherein more generally--in interdisciplinary fashion--developing resultssuch as: (1) analytic continuation (in complex $s$), (2) relevantcombinatorial identities, (3) rapidly converging series, (4) statisticalinferences, (5) connections to mathematical physics, and (6)extreme-precision quadrature techniques appropriate for these integrals.These intuitions and results open up avenues of experimental mathematics,with a view to new conjectures and theorems on integrals of thistype.

  4. Thirty-Year Solid Waste Generation Maximum and Minimum Forecast for SRS

    SciTech Connect

    Thomas, L.C.

    1994-10-01

    This report is the third phase (Phase III) of the Thirty-Year Solid Waste Generation Forecast for Facilities at the Savannah River Site (SRS). Phase I of the forecast, Thirty-Year Solid Waste Generation Forecast for Facilities at SRS, forecasts the yearly quantities of low-level waste (LLW), hazardous waste, mixed waste, and transuranic (TRU) wastes generated over the next 30 years by operations, decontamination and decommissioning and environmental restoration (ER) activities at the Savannah River Site. The Phase II report, Thirty-Year Solid Waste Generation Forecast by Treatability Group (U), provides a 30-year forecast by waste treatability group for operations, decontamination and decommissioning, and ER activities. In addition, a 30-year forecast by waste stream has been provided for operations in Appendix A of the Phase II report. The solid wastes stored or generated at SRS must be treated and disposed of in accordance with federal, state, and local laws and regulations. To evaluate, select, and justify the use of promising treatment technologies and to evaluate the potential impact to the environment, the generic waste categories described in the Phase I report were divided into smaller classifications with similar physical, chemical, and radiological characteristics. These smaller classifications, defined within the Phase II report as treatability groups, can then be used in the Waste Management Environmental Impact Statement process to evaluate treatment options. The waste generation forecasts in the Phase II report includes existing waste inventories. Existing waste inventories, which include waste streams from continuing operations and stored wastes from discontinued operations, were not included in the Phase I report. Maximum and minimum forecasts serve as upper and lower boundaries for waste generation. This report provides the maximum and minimum forecast by waste treatability group for operation, decontamination and decommissioning, and ER activities.

  5. Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets

    SciTech Connect

    Wong-Parodi, Gabrielle; Lekov, Alex; Dale, Larry

    2005-02-09

    This paper evaluates the accuracy of two methods to forecast natural gas prices: using the Energy Information Administration's ''Annual Energy Outlook'' forecasted price (AEO) and the ''Henry Hub'' compared to U.S. Wellhead futures price. A statistical analysis is performed to determine the relative accuracy of the two measures in the recent past. A statistical analysis suggests that the Henry Hub futures price provides a more accurate average forecast of natural gas prices than the AEO. For example, the Henry Hub futures price underestimated the natural gas price by 35 cents per thousand cubic feet (11.5 percent) between 1996 and 2003 and the AEO underestimated by 71 cents per thousand cubic feet (23.4 percent). Upon closer inspection, a liner regression analysis reveals that two distinct time periods exist, the period between 1996 to 1999 and the period between 2000 to 2003. For the time period between 1996 to 1999, AEO showed a weak negative correlation (R-square = 0.19) between forecast price by actual U.S. Wellhead natural gas price versus the Henry Hub with a weak positive correlation (R-square = 0.20) between forecasted price and U.S. Wellhead natural gas price. During the time period between 2000 to 2003, AEO shows a moderate positive correlation (R-square = 0.37) between forecasted natural gas price and U.S. Wellhead natural gas price versus the Henry Hub that show a moderate positive correlation (R-square = 0.36) between forecast price and U.S. Wellhead natural gas price. These results suggest that agencies forecasting natural gas prices should consider incorporating the Henry Hub natural gas futures price into their forecasting models along with the AEO forecast. Our analysis is very preliminary and is based on a very small data set. Naturally the results of the analysis may change, as more data is made available.

  6. Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

    Energy.gov [DOE]

    Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

  7. Weather Research and Forecasting Model with Vertical Nesting Capability

    Energy Science and Technology Software Center

    2014-08-01

    The Weather Research and Forecasting (WRF) model with vertical nesting capability is an extension of the WRF model, which is available in the public domain, from www.wrf-model.org. The new code modifies the nesting procedure, which passes lateral boundary conditions between computational domains in the WRF model. Previously, the same vertical grid was required on all domains, while the new code allows different vertical grids to be used on concurrently run domains. This new functionality improvesmore » WRF's ability to produce high-resolution simulations of the atmosphere by allowing a wider range of scales to be efficiently resolved and more accurate lateral boundary conditions to be provided through the nesting procedure.« less

  8. Wind Integration National Dataset (WIND) Toolkit; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    Draxl, Caroline; Hodge, Bri-Mathias

    2015-07-14

    A webinar about the Wind Integration National Dataset (WIND) Toolkit was presented by Bri-Mathias Hodge and Caroline Draxl on July 14, 2015. It was hosted by the Southern Alliance for Clean Energy. The toolkit is a grid integration data set that contains meteorological and power data at a 5-minute resolution across the continental United States for 7 years and hourly power forecasts.

  9. RADIATION INTEGRATOR

    DOEpatents

    Glass, F.M.; Wilson, H.N.

    1959-02-17

    Radiation detecting and measuring systems, particularly a compact, integrating, background monitor, are discussed. One of the principal features of the system is the use of an electrometer tube where the input of the tube is directly connected to an electrode of the radiation detector and a capacitor is coupled to the tube input. When a predetermined quantity of radiation has been integrated, a trigger signal is fed to a recorder and a charge is delivered to the capacitor to render the tube inoperative. The capacitor is then recharged for the next period of operation. With this arrangement there is a substantial reduction in lead lengths and the principal components may be enclosed and hermetically sealed to insure low leakage.

  10. Refinery Integration

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Mary Biddy Sue Jones NREL PNNL This presentation does not contain any proprietary, confidential, or otherwise restricted information DOE Bioenergy Technologies Office (BETO) 2015 Project Peer Review Refinery Integration 4.1.1.31 NREL 4.1.1.51 PNNL Goal Statement GOALS: Model bio-intermediates insertion points to better define costs & ID opportunities, technical risks, information gaps, research needs Publish results Review with stakeholders 2 Leveraging existing refining infrastructure

  11. U.S. oil production forecast revised up for 2016 and 2017

    Energy Information Administration (EIA) (indexed site)

    oil production forecast revised up for 2016 and 2017 U.S. crude oil production is expected to be higher this year and in 2017 than previously forecast, because of a slower decline in onshore production. In its new monthly forecast, the U.S. Energy Information Administration revised up its estimate for domestic oil production by about 110,000 barrels per day for 2016 and by 150,000 barrels per day next year. EIA said increased drilling activity in the Permian Basin area located in West Texas and

  12. World oil inventories forecast to grow significantly in 2016 and 2017

    Energy Information Administration (EIA) (indexed site)

    World oil inventories forecast to grow significantly in 2016 and 2017 Global oil inventories are expected to continue strong growth over the next two years which should keep oil prices low. In its new monthly forecast, the U.S. Energy Information Administration said world oil stocks are likely to increase by 1.6 million barrels per day this year and by 600,000 barrels per day next year. The higher forecast for inventory builds are the result of both higher global oil production and less oil

  13. Energy Department Announces $2.5 Million to Improve Wind Forecasting |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Improve Wind Forecasting Energy Department Announces $2.5 Million to Improve Wind Forecasting January 8, 2015 - 12:00pm Addthis The Energy Department today announced $2.5 million for a new project to research the atmospheric processes that generate wind in mountain-valley regions. This in-depth research, conducted by Vaisala of Louisville, Colorado, will be used to improve the wind industry's weather models for short-term wind forecasts, especially for those issued less

  14. Review of Variable Generation Forecasting in the West: July 2013 - March 2014

    SciTech Connect

    Widiss, R.; Porter, K.

    2014-03-01

    This report interviews 13 operating entities (OEs) in the Western Interconnection about their implementation of wind and solar forecasting. The report updates and expands upon one issued by NREL in 2012. As in the 2012 report, the OEs interviewed vary in size and character; the group includes independent system operators, balancing authorities, utilities, and other entities. Respondents' advice for other utilities includes starting sooner rather than later as it can take time to plan, prepare, and train a forecast; setting realistic expectations; using multiple forecasts; and incorporating several performance metrics.

  15. Medium term municipal solid waste generation prediction by autoregressive integrated moving average

    SciTech Connect

    Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan

    2014-09-12

    Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

  16. ACCELERATION INTEGRATOR

    DOEpatents

    Pope, K.E.

    1958-01-01

    This patent relates to an improved acceleration integrator and more particularly to apparatus of this nature which is gyrostabilized. The device may be used to sense the attainment by an airborne vehicle of a predetermined velocitv or distance along a given vector path. In its broad aspects, the acceleration integrator utilizes a magnetized element rotatable driven by a synchronous motor and having a cylin drical flux gap and a restrained eddy- current drag cap deposed to move into the gap. The angular velocity imparted to the rotatable cap shaft is transmitted in a positive manner to the magnetized element through a servo feedback loop. The resultant angular velocity of tae cap is proportional to the acceleration of the housing in this manner and means may be used to measure the velocity and operate switches at a pre-set magnitude. To make the above-described dcvice sensitive to acceleration in only one direction the magnetized element forms the spinning inertia element of a free gyroscope, and the outer housing functions as a gimbal of a gyroscope.

  17. Building America Efficient Solutions for New Homes Case Study: Tommy Williams Homes Initial Performance of Two Zero Energy Homes, Gainesville, Florida

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Description These high-performance homes in northern Florida are two that have achieved Home Energy Rating System (HERS) ratings of less than zero since Building America (BA) builders started building them in 2010. The homes (TW1 and TW2) were built in the Gainesville area by Tommy Williams Homes (TW), with technical assistance from Florida H.E.R.O. and energy-efficient home design input provided by Energy Smart Home Plans. The homes are being metered by the Florida Solar Energy Center (FSEC) as

  18. 1,"William F Wyman","Petroleum","FPL Energy Wyman LLC",811.3

    Energy Information Administration (EIA) (indexed site)

    Maine" ,"Plant","Primary energy source","Operating company","Net summer capacity (MW)" 1,"William F Wyman","Petroleum","FPL Energy Wyman LLC",811.3 2,"Westbrook Energy Center Power Plant","Natural gas","Westbrook Energy Center",506 3,"Maine Independence Station","Natural gas","Casco Bay Energy Co LLC",490 4,"Bucksport Generation LLC","Natural

  19. William J. Clinton, 1995

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    The Emergency Planning and Community Right-to-Know Act of 1986 (42 U.S.C. 11001-11050) (''EPCRA'') and the Pollution Prevention Act of 1990 (42 U.S.C. 13101- 13109) (''PPA'') ...

  20. Brian P. Williams

    Office of Scientific and Technical Information (OSTI)

    This interferometer also allows for a unique version of the CHSH-Bell test where the local ... a Clauser-Horne-Shimony-Holt (CHSH) Bell test 8, with entanglement detected for Bell ...

  1. William J. Clinton, 2000

    Office of Environmental Management (EM)

    ... funds to reduce poverty and provide basic health care and education for their people. ... tality, improve health, expand educational opportunities, and lift people out of poverty. ...

  2. William T. Yardley

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy"s efforts to address natural gas pipeline constraints in New England, and how ... natural gas, natural gas liquids, and crude oil pipelines, approximately 305 billion ...

  3. Williams_1992.pdf

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

  4. William J. Clinton, 2000

    Energy Saver

    I sent a budget this year to the Congress to provide significant new resources to fight climate change and air and water pollution. My lands legacy initiative would provide record ...

  5. William J. Clinton, 1998

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ... To the extent feasible, remote sensing capabilities shall be developed and applied to this ... identifying the major causes and consequences of degrada- tion of coral reef ecosystems. ...

  6. U.S. diesel fuel price forecast to be 1 penny lower this summer...

    Energy Information Administration (EIA) (indexed site)

    That's down 12 percent from last summer's record exports. Biodiesel production, which averaged 68,000 barrels a day last summer, is forecast to jump to 82,000 barrels a day this ...

  7. Energy Savings Forecast of Solid-State Lighting in General Illumination Applications

    Office of Energy Efficiency and Renewable Energy (EERE)

    Report forecasting the U.S. energy savings of LED white-light sources compared to conventional white-light sources (i.e., incandescent, halogen, fluorescent, and high-intensity discharge) over the...

  8. Examining Information Entropy Approaches as Wind Power Forecasting Performance Metrics: Preprint

    SciTech Connect

    Hodge, B. M.; Orwig, K.; Milligan, M.

    2012-06-01

    In this paper, we examine the parameters associated with the calculation of the Renyi entropy in order to further the understanding of its application to assessing wind power forecasting errors.

  9. U.S. Crude Oil Production Forecast-Analysis of Crude Types

    Energy Information Administration (EIA) (indexed site)

    of Energy Washington, DC 20585 U.S. Energy Information Administration | U.S. Crude Oil Production Forecast-Analysis of Crude Types i This report was prepared by the U.S....

  10. Gasoline price forecast to stay below 3 dollar a gallon in 2015

    Energy Information Administration (EIA) (indexed site)

    Gasoline price forecast to stay below 3 a gallon in 2015 The national average pump price of gasoline is expected to stay below 3 per gallon during 2015. In its new monthly ...

  11. NREL: Energy Systems Integration - Systems Integration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    High-level system integration New distribution scenarios such as household DC systems and residential-scale generation and storage integrated with home energy management systems. ...

  12. NREL: Transmission Grid Integration - Wind Integration Datasets

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Wind Integration Datasets The datasets below provide energy professionals with a consistent set of ... Eastern and Western Wind Datasets WIND Toolkit Solar Integration Datasets ...

  13. Energy Systems Integration | NREL

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Electricity to Grid Integration Vehicle to Grid Integration Renewable Fuels to Grid Integration Battery & Thermal Energy Storage Microgrids Cybersecurity & Resilience Smart ...

  14. Solar energy conversion: Technological forecasting. (Latest citations from the Aerospace database). Published Search

    SciTech Connect

    Not Available

    1993-12-01

    The bibliography contains citations concerning current forecasting of Earth surface-bound solar energy conversion technology. Topics consider research, development and utilization of this technology in relation to electric power generation, heat pumps, bioconversion, process heat and the production of renewable gaseous, liquid, and solid fuels for industrial, commercial, and domestic applications. Some citations concern forecasts which compare solar technology with other energy technologies. (Contains 250 citations and includes a subject term index and title list.)

  15. Solar energy conversion: Technological forecasting. (Latest citations from the Aerospace database). Published Search

    SciTech Connect

    1995-01-01

    The bibliography contains citations concerning current forecasting of Earth surface-bound solar energy conversion technology. Topics consider research, development and utilization of this technology in relation to electric power generation, heat pumps, bioconversion, process heat and the production of renewable gaseous, liquid, and solid fuels for industrial, commercial, and domestic applications. Some citations concern forecasts which compare solar technology with other energy technologies. (Contains 250 citations and includes a subject term index and title list.)

  16. Investigating the Correlation Between Wind and Solar Power Forecast Errors in the Western Interconnection: Preprint

    SciTech Connect

    Zhang, J.; Hodge, B. M.; Florita, A.

    2013-05-01

    Wind and solar power generations differ from conventional energy generation because of the variable and uncertain nature of their power output. This variability and uncertainty can have significant impacts on grid operations. Thus, short-term forecasting of wind and solar generation is uniquely helpful for power system operations to balance supply and demand in an electricity system. This paper investigates the correlation between wind and solar power forecasting errors.

  17. Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE (Presentation)

    SciTech Connect

    Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B.M.

    2014-11-01

    The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This presentation is an overview of a study that examines the value of improved solar forecasts on Bulk Power System Operations.

  18. Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE: Preprint

    SciTech Connect

    Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B. M.

    2014-09-01

    The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This study examines the value of improved solar power forecasting for the Independent System Operator-New England system. The results show how 25% solar power penetration reduces net electricity generation costs by 22.9%.

  19. U.S. Department of Energy Workshop Report: Solar Resources and Forecasting

    SciTech Connect

    Stoffel, T.

    2012-06-01

    This report summarizes the technical presentations, outlines the core research recommendations, and augments the information of the Solar Resources and Forecasting Workshop held June 20-22, 2011, in Golden, Colorado. The workshop brought together notable specialists in atmospheric science, solar resource assessment, solar energy conversion, and various stakeholders from industry and academia to review recent developments and provide input for planning future research in solar resource characterization, including measurement, modeling, and forecasting.

  20. Advancements in Wind Integration Study Data Modeling: The Wind Integration National Dataset (WIND) Toolkit; Preprint

    SciTech Connect

    Draxl, C.; Hodge, B. M.; Orwig, K.; Jones, W.; Searight, K.; Getman, D.; Harrold, S.; McCaa, J.; Cline, J.; Clark, C.

    2013-10-01

    Regional wind integration studies in the United States require detailed wind power output data at many locations to perform simulations of how the power system will operate under high-penetration scenarios. The wind data sets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as be time synchronized with available load profiles. The Wind Integration National Dataset (WIND) Toolkit described in this paper fulfills these requirements. A wind resource dataset, wind power production time series, and simulated forecasts from a numerical weather prediction model run on a nationwide 2-km grid at 5-min resolution will be made publicly available for more than 110,000 onshore and offshore wind power production sites.

  1. The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations. The Southern Study Area, Final Report

    SciTech Connect

    Freedman, Jeffrey M.; Manobianco, John; Schroeder, John; Ancell, Brian; Brewster, Keith; Basu, Sukanta; Banunarayanan, Venkat; Hodge, Bri-Mathias; Flores, Isabel

    2014-04-30

    This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP) -- Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute - 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 - 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 - 3 hours.

  2. Smart Grid Educational Series | Energy Systems Integration |...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    ... William J. Miller, President of MaCT USA, hosted a webinar on April 13, 2016, on the Internet of Things (IoT) and PowerMatcher Transactive Energy for smart cities. Download ...

  3. Grid Integration of Aggregated Demand Response, Part 2: Modeling Demand Response in a Production Cost Model

    Energy.gov [DOE]

    Renewable integration studies have evaluated many challenges associated with deploying large amounts of variable wind and solar generation technologies. These studies can evaluate operational impacts associated with variable generation, benefits of improved wind and solar resource forecasting, and trade-offs between institutional changes, including increasing balancing area cooperation and technical changes such as installing new flexible generation. Demand response (DR) resources present a potentially important source of grid flexibility and can aid in integrating variable generation; however, integration analyses have not yet incorporated these resources explicitly into grid simulation models as part of a standard toolkit for resource planners.

  4. Market-Based Indian Grid Integration Study Options: Preprint

    SciTech Connect

    Stoltenberg, B.; Clark, K.; Negi, S. K.

    2012-03-01

    The Indian state of Gujarat is forecasting solar and wind generation expansion from 16% to 32% of installed generation capacity by 2015. Some states in India are already experiencing heavy wind power curtailment. Understanding how to integrate variable generation (VG) into the grid is of great interest to local transmission companies and India's Ministry of New and Renewable Energy. This paper describes the nature of a market-based integration study and how this approach, while new to Indian grid operation and planning, is necessary to understand how to operate and expand the grid to best accommodate the expansion of VG. Second, it discusses options in defining a study's scope, such as data granularity, generation modeling, and geographic scope. The paper also explores how Gujarat's method of grid operation and current system reliability will affect how an integration study can be performed.

  5. Final Report on California Regional Wind Energy Forecasting Project:Application of NARAC Wind Prediction System

    SciTech Connect

    Chin, H S

    2005-07-26

    Wind power is the fastest growing renewable energy technology and electric power source (AWEA, 2004a). This renewable energy has demonstrated its readiness to become a more significant contributor to the electricity supply in the western U.S. and help ease the power shortage (AWEA, 2000). The practical exercise of this alternative energy supply also showed its function in stabilizing electricity prices and reducing the emissions of pollution and greenhouse gases from other natural gas-fired power plants. According to the U.S. Department of Energy (DOE), the world's winds could theoretically supply the equivalent of 5800 quadrillion BTUs of energy each year, which is 15 times current world energy demand (AWEA, 2004b). Archer and Jacobson (2005) also reported an estimation of the global wind energy potential with the magnitude near half of DOE's quote. Wind energy has been widely used in Europe; it currently supplies 20% and 6% of Denmark's and Germany's electric power, respectively, while less than 1% of U.S. electricity is generated from wind (AWEA, 2004a). The production of wind energy in California ({approx}1.2% of total power) is slightly higher than the national average (CEC & EPRI, 2003). With the recently enacted Renewable Portfolio Standards calling for 20% of renewables in California's power generation mix by 2010, the growth of wind energy would become an important resource on the electricity network. Based on recent wind energy research (Roulston et al., 2003), accurate weather forecasting has been recognized as an important factor to further improve the wind energy forecast for effective power management. To this end, UC-Davis (UCD) and LLNL proposed a joint effort through the use of UCD's wind tunnel facility and LLNL's real-time weather forecasting capability to develop an improved regional wind energy forecasting system. The current effort of UC-Davis is aimed at developing a database of wind turbine power curves as a function of wind speed and

  6. Review of the Sodium Bearing Waste Treatment Project - Integrated...

    Office of Environmental Management (EM)

    Review OSO Outside Support Operator POA Plan of Action SAC Specific Administrative Control SAR Safety Analysis Report ... Quality Review Board William Eckroade John ...

  7. Demand forecasting for automotive sector in Malaysia by system dynamics approach

    SciTech Connect

    Zulkepli, Jafri Abidin, Norhaslinda Zainal; Fong, Chan Hwa

    2015-12-11

    In general, Proton as an automotive company needs to forecast future demand of the car to assist in decision making related to capacity expansion planning. One of the forecasting approaches that based on judgemental or subjective factors is normally used to forecast the demand. As a result, demand could be overstock that eventually will increase the operation cost; or the company will face understock, which resulted losing their customers. Due to automotive industry is very challenging process because of high level of complexity and uncertainty involved in the system, an accurate tool to forecast the future of automotive demand from the modelling perspective is required. Hence, the main objective of this paper is to forecast the demand of automotive Proton car industry in Malaysia using system dynamics approach. Two types of intervention namely optimistic and pessimistic experiments scenarios have been tested to determine the capacity expansion that can prevent the company from overstocking. Finding from this study highlighted that the management needs to expand their production for optimistic scenario, whilst pessimistic give results that would otherwise. Finally, this study could help Proton Edar Sdn. Bhd (PESB) to manage the long-term capacity planning in order to meet the future demand of the Proton cars.

  8. Optimization Based Data Mining Approah for Forecasting Real-Time Energy Demand

    SciTech Connect

    Omitaomu, Olufemi A; Li, Xueping; Zhou, Shengchao

    2015-01-01

    The worldwide concern over environmental degradation, increasing pressure on electric utility companies to meet peak energy demand, and the requirement to avoid purchasing power from the real-time energy market are motivating the utility companies to explore new approaches for forecasting energy demand. Until now, most approaches for forecasting energy demand rely on monthly electrical consumption data. The emergence of smart meters data is changing the data space for electric utility companies, and creating opportunities for utility companies to collect and analyze energy consumption data at a much finer temporal resolution of at least 15-minutes interval. While the data granularity provided by smart meters is important, there are still other challenges in forecasting energy demand; these challenges include lack of information about appliances usage and occupants behavior. Consequently, in this paper, we develop an optimization based data mining approach for forecasting real-time energy demand using smart meters data. The objective of our approach is to develop a robust estimation of energy demand without access to these other building and behavior data. Specifically, the forecasting problem is formulated as a quadratic programming problem and solved using the so-called support vector machine (SVM) technique in an online setting. The parameters of the SVM technique are optimized using simulated annealing approach. The proposed approach is applied to hourly smart meters data for several residential customers over several days.

  9. The Wind Integration National Dataset (WIND) toolkit (Presentation)

    SciTech Connect

    Caroline Draxl: NREL

    2014-01-01

    Regional wind integration studies require detailed wind power output data at many locations to perform simulations of how the power system will operate under high penetration scenarios. The wind datasets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as being time synchronized with available load profiles.As described in this presentation, the WIND Toolkit fulfills these requirements by providing a state-of-the-art national (US) wind resource, power production and forecast dataset.

  10. Integrating Solar PV in Utility System Operations

    SciTech Connect

    Mills, A.; Botterud, A.; Wu, J.; Zhou, Z.; Hodge, B-M.; Heany, M.

    2013-10-31

    This study develops a systematic framework for estimating the increase in operating costs due to uncertainty and variability in renewable resources, uses the framework to quantify the integration costs associated with sub-hourly solar power variability and uncertainty, and shows how changes in system operations may affect these costs. Toward this end, we present a statistical method for estimating the required balancing reserves to maintain system reliability along with a model for commitment and dispatch of the portfolio of thermal and renewable resources at different stages of system operations. We estimate the costs of sub-hourly solar variability, short-term forecast errors, and day-ahead (DA) forecast errors as the difference in production costs between a case with “realistic” PV (i.e., subhourly solar variability and uncertainty are fully included in the modeling) and a case with “well behaved” PV (i.e., PV is assumed to have no sub-hourly variability and can be perfectly forecasted). In addition, we highlight current practices that allow utilities to compensate for the issues encountered at the sub-hourly time frame with increased levels of PV penetration. In this analysis we use the analytical framework to simulate utility operations with increasing deployment of PV in a case study of Arizona Public Service Company (APS), a utility in the southwestern United States. In our analysis, we focus on three processes that are important in understanding the management of PV variability and uncertainty in power system operations. First, we represent the decisions made the day before the operating day through a DA commitment model that relies on imperfect DA forecasts of load and wind as well as PV generation. Second, we represent the decisions made by schedulers in the operating day through hour-ahead (HA) scheduling. Peaking units can be committed or decommitted in the HA schedules and online units can be redispatched using forecasts that are improved

  11. NREL: Energy Systems Integration Facility - Systems Integration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Systems Integration Systems integration considers the relationships among electricity, thermal, and fuel systems and data and information networks to ensure optimal interoperability across the energy spectrum. The Energy Systems Integration Facility's suite of systems integration laboratories provides advanced capabilities for research, development, and demonstration of key components of future energy systems. Photo of a man and a power quality meter system in a laboratory. The Energy Systems

  12. Roel Neggers European Centre for Medium-range Weather Forecasts

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Roderick Jackson About Us Roderick Jackson - Technical Lead, Oak Ridge National Lab Roderick Jackson leads the Building Envelope Systems Research Group at the Department of Energy's Oak Ridge National Laboratory and serves as the technical lead for the Additive Manufacturing Integrated Energy (AMIE) demonstration project. He holds a bachelor's, master's, and Ph.D. in mechanical engineering from Georgia Tech. More about the AMIE demonstration project can be found:

  13. Baseline data for the residential sector and development of a residential forecasting database

    SciTech Connect

    Hanford, J.W.; Koomey, J.G.; Stewart, L.E.; Lecar, M.E.; Brown, R.E.; Johnson, F.X.; Hwang, R.J.; Price, L.K.

    1994-05-01

    This report describes the Lawrence Berkeley Laboratory (LBL) residential forecasting database. It provides a description of the methodology used to develop the database and describes the data used for heating and cooling end-uses as well as for typical household appliances. This report provides information on end-use unit energy consumption (UEC) values of appliances and equipment historical and current appliance and equipment market shares, appliance and equipment efficiency and sales trends, cost vs efficiency data for appliances and equipment, product lifetime estimates, thermal shell characteristics of buildings, heating and cooling loads, shell measure cost data for new and retrofit buildings, baseline housing stocks, forecasts of housing starts, and forecasts of energy prices and other economic drivers. Model inputs and outputs, as well as all other information in the database, are fully documented with the source and an explanation of how they were derived.

  14. Integrated DC-DC Converters Using Thin-Film Magnetic Power Inductors

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    PRODUCTS PROVIDE COST, POWER, AREA SAVINGS FOR SERVERS, MOBILE DEVICES, WEARABLES AND IOT  Ferric's technology improves upon existing power delivery infrastructure by down-converting power in immediate proximity to the load  Worldwide market for discrete power components plus integrated switching voltage regulator components is forecast at US$36B in 2020 4 | June 2016 | Ferric, Inc. | DE-SC0009200 Fe  Fabless semiconductor technology company, founded in 2011  Located in New York City

  15. Analysis of Cycling Costs in Western Wind and Solar Integration Study

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    SR/OIAF/2008-03 Analysis of Crude Oil Production in the Arctic National Wildlife Refuge May 2008 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as

  16. Forecasting longitudinal changes in oropharyngeal tumor morphology throughout the course of head and neck radiation therapy

    SciTech Connect

    Yock, Adam D.; Kudchadker, Rajat J.; Rao, Arvind; Dong, Lei; Beadle, Beth M.; Garden, Adam S.; Court, Laurence E.

    2014-08-15

    Purpose: To create models that forecast longitudinal trends in changing tumor morphology and to evaluate and compare their predictive potential throughout the course of radiation therapy. Methods: Two morphology feature vectors were used to describe 35 gross tumor volumes (GTVs) throughout the course of intensity-modulated radiation therapy for oropharyngeal tumors. The feature vectors comprised the coordinates of the GTV centroids and a description of GTV shape using either interlandmark distances or a spherical harmonic decomposition of these distances. The change in the morphology feature vector observed at 33 time points throughout the course of treatment was described using static, linear, and mean models. Models were adjusted at 0, 1, 2, 3, or 5 different time points (adjustment points) to improve prediction accuracy. The potential of these models to forecast GTV morphology was evaluated using leave-one-out cross-validation, and the accuracy of the models was compared using Wilcoxon signed-rank tests. Results: Adding a single adjustment point to the static model without any adjustment points decreased the median error in forecasting the position of GTV surface landmarks by the largest amount (1.2 mm). Additional adjustment points further decreased the forecast error by about 0.4 mm each. Selection of the linear model decreased the forecast error for both the distance-based and spherical harmonic morphology descriptors (0.2 mm), while the mean model decreased the forecast error for the distance-based descriptor only (0.2 mm). The magnitude and statistical significance of these improvements decreased with each additional adjustment point, and the effect from model selection was not as large as that from adding the initial points. Conclusions: The authors present models that anticipate longitudinal changes in tumor morphology using various models and model adjustment schemes. The accuracy of these models depended on their form, and the utility of these models

  17. Summer gasoline price forecast slightly higher, but drivers still pay less than last year

    Energy Information Administration (EIA) (indexed site)

    Summer gasoline price forecast slightly higher, but drivers still pay less than last year Rising crude oil prices are likely to be passed on to consumers at the pump, but U.S. drivers are still expected to pay the lowest summer gasoline prices since 2004, and for all of 2016 the average household will spend $900 less on gasoline than it did two years ago." In its new monthly forecast, the U.S. Energy Information Administration said the retail price for regular grade gasoline will average

  18. ARM - Field Campaign - 915 MHz Wind Profiler for Cloud Forecasting at BNL

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    govCampaigns915 MHz Wind Profiler for Cloud Forecasting at BNL Campaign Links Field Campaign Report ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : 915 MHz Wind Profiler for Cloud Forecasting at BNL 2011.05.31 - 2012.05.31 Lead Scientist : Michael Jensen For data sets, see below. Abstract In support of the installation of a 37 MW solar array on the grounds of Brookhaven National Laboratory (BNL), a study

  19. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04

    On December 14, 2009, the reference-case projections from Annual Energy Outlook 2010 were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in itigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings.

  20. EERE Success Story-Solar Forecasting Gets a Boost from Watson, Accuracy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Improved by 30% | Department of Energy Forecasting Gets a Boost from Watson, Accuracy Improved by 30% EERE Success Story-Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am Addthis IBM Youtube Video | Courtesy of IBM Remember when IBM's super computer Watson defeated Jeopardy! champions Ken Jennings and Brad Rutter? With funding from the U.S. Department of Energy SunShot Initiative, IBM researchers are using Watson-like technology to improve solar

  1. ARM - Field Campaign - Radar Wind Profiler for Cloud Forecasting at BNL

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    govCampaignsRadar Wind Profiler for Cloud Forecasting at BNL Campaign Links Field Campaign Report ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Radar Wind Profiler for Cloud Forecasting at BNL 2013.07.15 - 2015.08.06 Lead Scientist : Michael Jensen For data sets, see below. Abstract In support of recent activities funded by the DOE Energy Efficiency and Renewable Energy (EERE) to produce short-term

  2. Distribution Grid Integration

    Energy.gov [DOE]

    The DOE Systems Integration team funds distribution grid integration research and development (R&D) activities to address the technical issues that surround distribution grid planning,...

  3. Thermal Control & System Integration

    Energy.gov [DOE]

    The thermal control and system integration activity focuses on issues such as the integration of motor and power control technologies and the development of advanced thermal control technologies....

  4. Integrating Environmental Stewardship

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    stewardship Many Laboratory functions are integrated with environmental stewardship. This Strategy cannot be effective without systematic integration with other related Laboratory...

  5. Upstream Measurements of Wind Profiles with Doppler Lidar for Improved Wind Energy Integration

    SciTech Connect

    Rodney Frehlich

    2012-10-30

    New upstream measurements of wind profiles over the altitude range of wind turbines will be produced using a scanning Doppler lidar. These long range high quality measurements will provide improved wind power forecasts for wind energy integration into the power grid. The main goal of the project is to develop the optimal Doppler lidar operating parameters and data processing algorithms for improved wind energy integration by enhancing the wind power forecasts in the 30 to 60 minute time frame, especially for the large wind power ramps. Currently, there is very little upstream data at large wind farms, especially accurate wind profiles over the full height of the turbine blades. The potential of scanning Doppler lidar will be determined by rigorous computer modeling and evaluation of actual Doppler lidar data from the WindTracer system produced by Lockheed Martin Coherent Technologies, Inc. of Louisville, Colorado. Various data products will be investigated for input into numerical weather prediction models and statistically based nowcasting algorithms. Successful implementation of the proposed research will provide the required information for a full cost benefit analysis of the improved forecasts of wind power for energy integration as well as the added benefit of high quality wind and turbulence information for optimal control of the wind turbines at large wind farms.

  6. Sandia Energy - Transmission Grid Integration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Transmission Grid Integration Home Stationary Power Energy Conversion Efficiency Solar Energy Photovoltaics Grid Integration Transmission Grid Integration Transmission Grid...

  7. Sandia Energy - Distribution Grid Integration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Distribution Grid Integration Home Stationary Power Energy Conversion Efficiency Solar Energy Photovoltaics Grid Integration Distribution Grid Integration Distribution Grid...

  8. Industrial end-use forecasting that incorporates DSM and air quality

    SciTech Connect

    Tutt, T.; Flory, J.

    1995-05-01

    The California Energy Commission (CEC) and major enregy utilities in California have generally depended on simple aggregate intensity or economic models to forecast energy use in the process industry sector (which covers large industries employing basic processes to transform raw materials, such as paper mills, glass plants, and cement plants). Two recent trends suggests that the time has come to develop a more disaggregate process industry forecasting model. First, recent efforts to improve air quality, especially by the South Coast Air Quality Management District (SCAQMD), could significantly affect energy use by the process industry by altering the technologies and processes employed in order to reduce emissions. Second, there is a renewed interest in Demand-Side Management (DSM), not only for utility least-cost planning, but also for improving the economic competitiveness and environmental compliance of the pro{minus}cess industries. A disaggregate forecasting model is critical to help the CEC and utilities evaluate both the air quality and DSM impacts on energy use. A crucial obstacle to the development and use of these detailed process industry forecasting models is the lack of good data about disaggregate energy use in the sector. The CEC is nearing completion of a project to begin to overcome this lack of data. The project is testing methds of developing detailed energy use data, collecting an initial database for a large portion of southern California, and providing recommendations and direction for further data collection efforts.

  9. Expectations models of electric utilities' forecasts: a case study of econometric estimation with influential data points

    SciTech Connect

    Vellutini, R. de A.S.; Mount, T.D.

    1983-01-01

    This study develops an econometric model for explaining how electric utilities revise their forecasts of future electricity demand each year. The model specification is developed from the adaptive expectations hypothesis and it relates forecasted growth rates to actual lagged growth rates of electricity demand. Unlike other studies of the expectation phenomenon, expectations of future demand levels constitute an observable variable and thus can be incorporated explicitly into the model. The data used for the analysis were derived from the published forecasts of the nine National Electric Reliability Councils in the US for the years 1974 to 1980. Three alternative statistical methods are used for estimation purposes: ordinary least-squares, robust regression and a diagnostic analysis to identify influential observations. The results obtained with the first two methods are very similar, but are both inconsistent with the underlying economic logic of the model. The estimated model obtained from the diagnostics approach after deleting two aberrant observations is consistent with economic logic, and supports the hypothesis that the low growth demand experienced immediately following the oil embargo in 1973 were disregarded by the industry for forecasting purposes. The model includes transitory effects associated with the oil embargo that gradually disappear over time, the estimated coefficients for the lagged values of actual growth approach a structure with declining positive weights. The general shape of this asymptotic structure is similar to the findings in many economic applications using distributed lag models.

  10. Procurement Integrity Brochure What is Procurement Integrity?

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Procurement Integrity Brochure What is Procurement Integrity? The Department of Energy, like most federal agencies, purchases many products and services from the private sector. To preserve the integrity of the Federal procurement process and assure fair treatment of bidders, offerors, and contractors, laws govern the procurement process and the manner in which federal and contractor personnel conduct business with each other. One of these statutes is Section 27 of the Office of Federal

  11. Energy Systems Integration Newsletter | Energy Systems Integration...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    INTEGRATE Project Partner Demonstrates Clean Energy Interconnection Solution at the ESIF ... first to model the entire Eastern Interconnection at 5-minute intervals for a full ...

  12. NREL: Transmission Grid Integration - Wind Integration National...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    of Energy Efficiency and Renewable Energy, Wind and Water Power Technologies Office, and ... Principles for Integration Studies Glossary News Did you find what you needed? ...

  13. Experimental Data from the Proteomics Research Center for Integrative Biology

    DOE Data Explorer

    Smith, Richard D.

    The possible roles and importance of proteomics are rapidly growing across essentially all areas of biological research. The precise and comprehensive measurement of levels of expressed proteins and their modified forms can provide new insights into the molecular nature of cell-signaling pathways and networks, the cell cycle, cellular differentiation, and other processes relevant to understanding human health and the progression of various disease states. The ability to characterize protein complexes complements this capability, allowing hypotheses to be tested and the biological system operation to be defined. The Proteomics Research Center for Integrative Biology is a national user facility established and funded by the National Institute of General Medical Sciences component of the National Institutes of Health. This Center has been established to serve the biomedical research community by developing and integrating new proteomic technologies for collaborative and service studies, disseminating the new technologies, and training scientists in their use. The Center is housed in DOEs William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) at the Pacific Northwest National Laboratory.

  14. Experimental Data from the Proteomics Research Center for Integrative Biology

    DOE Data Explorer

    Smith, Richard D.

    The possible roles and importance of proteomics are rapidly growing across essentially all areas of biological research. The precise and comprehensive measurement of levels of expressed proteins and their modified forms can provide new insights into the molecular nature of cell-signaling pathways and networks, the cell cycle, cellular differentiation, and other processes relevant to understanding human health and the progression of various disease states. The ability to characterize protein complexes complements this capability, allowing hypotheses to be tested and the biological system operation to be defined. The Proteomics Research Center for Integrative Biology is a national user facility established and funded by the National Institute of General Medical Sciences component of the National Institutes of Health. This Center has been established to serve the biomedical research community by developing and integrating new proteomic technologies for collaborative and service studies, disseminating the new technologies, and training scientists in their use. The Center is housed in DOE’s William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) at the Pacific Northwest National Laboratory.

  15. Integration of Uncertainty Information into Power System Operations

    SciTech Connect

    Makarov, Yuri V.; Lu, Shuai; Samaan, Nader A.; Huang, Zhenyu; Subbarao, Krishnappa; Etingov, Pavel V.; Ma, Jian; Hafen, Ryan P.; Diao, Ruisheng; Lu, Ning

    2011-10-10

    Contemporary power systems face uncertainties coming from multiple sources, including forecast errors of load, wind and solar generation, uninstructed deviation and forced outage of traditional generators, loss of transmission lines, and others. With increasing amounts of wind and solar generation being integrated into the system, these uncertainties have been growing significantly. It is critical important to build knowledge of major sources of uncertainty, learn how to simulate them, and then incorporate this information into the decision-making processes and power system operations, for better reliability and efficiency. This paper gives a comprehensive view on the sources of uncertainty in power systems, important characteristics, available models, and ways of their integration into system operations. It is primarily based on previous works conducted at the Pacific Northwest National Laboratory (PNNL).

  16. A Distributed Modeling System for Short-Term to Seasonal Ensemble Streamflow Forecasting in Snowmelt Dominated Basins

    SciTech Connect

    Wigmosta, Mark S.; Gill, Muhammad K.; Coleman, Andre M.; Prasad, Rajiv; Vail, Lance W.

    2007-12-01

    This paper describes a distributed modeling system for short-term to seasonal water supply forecasts with the ability to utilize remotely-sensed snow cover products and real-time streamflow measurements. Spatial variability in basin characteristics and meteorology is represented using a raster-based computational grid. Canopy interception, snow accumulation and melt, and simplified soil water movement are simulated in each computational unit. The model is run at a daily time step with surface runoff and subsurface flow aggregated at the basin scale. This approach allows the model to be updated with spatial snow cover and measured streamflow using an Ensemble Kalman-based data assimilation strategy that accounts for uncertainty in weather forecasts, model parameters, and observations used for updating. Model inflow forecasts for the Dworshak Reservoir in northern Idaho are compared to observations and to April-July volumetric forecasts issued by the Natural Resource Conservation Service (NRCS) for Water Years 2000 2006. October 1 volumetric forecasts are superior to those issued by the NRCS, while March 1 forecasts are comparable. The ensemble spread brackets the observed April-July volumetric inflows in all years. Short-term (one and three day) forecasts also show excellent agreement with observations.

  17. Application of Ensemble Sensitivity Analysis to Observation Targeting for Short-term Wind Speed Forecasting

    SciTech Connect

    Zack, J; Natenberg, E; Young, S; Manobianco, J; Kamath, C

    2010-02-21

    The operators of electrical grids, sometimes referred to as Balancing Authorities (BA), typically make critical decisions on how to most reliably and economically balance electrical load and generation in time frames ranging from a few minutes to six hours ahead. At higher levels of wind power generation, there is an increasing need to improve the accuracy of 0- to 6-hour ahead wind power forecasts. Forecasts on this time scale have typically been strongly dependent on short-term trends indicated by the time series of power production and meteorological data from a wind farm. Additional input information is often available from the output of Numerical Weather Prediction (NWP) models and occasionally from off-site meteorological towers in the region surrounding the wind generation facility. A widely proposed approach to improve short-term forecasts is the deployment of off-site meteorological towers at locations upstream from the wind generation facility in order to sense approaching wind perturbations. While conceptually appealing, it turns out that, in practice, it is often very difficult to derive significant benefit in forecast performance from this approach. The difficulty is rooted in the fact that the type, scale, and amplitude of the processes controlling wind variability at a site change from day to day if not from hour to hour. Thus, a location that provides some useful forecast information for one time may not be a useful predictor a few hours later. Indeed, some processes that cause significant changes in wind power production operate predominantly in the vertical direction and thus cannot be monitored by employing a network of sensors at off-site locations. Hence, it is very challenging to determine the type of sensors and deployment locations to get the most benefit for a specific short-term forecast application. Two tools recently developed in the meteorological research community have the potential to help determine the locations and parameters to

  18. EIA revises up forecast for U.S. 2013 crude oil production by 70,000 barrels per day

    Energy Information Administration (EIA) (indexed site)

    EIA revises up forecast for U.S. 2013 crude oil production by 70,000 barrels per day The forecast for U.S. crude oil production keeps going higher. The U.S. Energy Information Administration revised upward its projection for crude oil output in 2013 by 70,000 barrels per day and for next year by 190,000 barrels per day. U.S. oil production is now on track to average 7.5 million barrels per day this year and rise to 8.4 million barrels per day in 2014, according to EIA's latest monthly forecast.

  19. A Processor to get UV-A and UV-B Radiation Products from the ECMWF Forecast

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    System A Processor to get UV-A and UV-B Radiation Products from the ECMWF Forecast System Morcrette, Jean-Jacques European Centre for Medium-Range Weather Forecasts Category: Radiation A new processor for evaluating the UV-B and UV-A radiation at the surface, based on modifications to the current shortwave radiation scheme of the ECMWF forecast system is described. Sensitivity studies of the UV surface irradiance and Erythemal Dose Rate to spectral resolution, representation and atmospheric

  20. Demonstration Assessment of Light Emitting Diode (LED) Walkway Lighting at the Federal Aviation Administration William J. Hughes Technical Center, in Atlantic City, New Jersey

    SciTech Connect

    Kinzey, Bruce R.; Myer, Michael

    2008-03-18

    This report documents the results of a collaborative project to demonstrate a solid state lighting (SSL) general illumination product in an outdoor area walkway application. In the project, six light-emitting diode (LED) luminaires were installed to replace six existing high pressure sodium (HPS) luminaires mounted on 14-foot poles on a set of exterior walkways and stairs at the Federal Aviation Administration (FAA) William J. Hughes Technical Center in Atlantic City, New Jersey, during December, 2007. The effort was a U.S. Department of Energy (DOE) SSL Technology Gateway Demonstration that involved a collaborative teaming agreement between DOE, FAA and Ruud Lighting (and their wholly owned division, Beta LED). Pre- and post-installation power and illumination measurements were taken and used in calculations of energy savings and related economic payback, while personnel impacted by the new lights were provided questionnaires to gauge their perceptions and feedback. The SSL product demonstrated energy savings of over 25% while maintaining illuminance levels and improving illuminance uniformity. PNNL's economic analysis yielded a variety of potential payback results depending on the assumptions used. In the best case, replacing HPS with the LED luminaire can yield a payback as low as 3 years. The new lamps were quite popular with the affected personnel, who gave the lighting an average score of 4.46 out of 5 for improvement.

  1. Integrating Environmental Stewardship

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Consent-Based Siting » Integrated Waste Management Integrated Waste Management The Department envisions an integrated waste management system with storage, transportation, and disposal capabilities in order to safely and effectively manage our nation's spent nuclear fuel and high-level radioactive waste. The Department envisions an integrated waste management system with storage, transportation, and disposal capabilities in order to safely and effectively manage our nation's spent nuclear fuel

  2. Integration of Photovoltaics into Building Energy Usage through Advanced Control of Rooftop Unit

    SciTech Connect

    Starke, Michael R; Nutaro, James J; Irminger, Philip; Ollis, Benjamin; Kuruganti, Phani Teja; Fugate, David L

    2014-01-01

    This paper presents a computational approach to forecast photovoltaic (PV) power in kW based on a neural network linkage of publicly available cloud cover data and on-site solar irradiance sensor data. We also describe a control approach to utilize rooftop air conditioning units (RTUs) to support renewable integration. The PV forecasting method is validated using data from a rooftop PV panel installed on the Distributed Energy, Communications, and Controls (DECC) laboratory at Oak Ridge National Laboratory. The validation occurs in multiple phases to ensure that each component of the approach is the best representation of the actual expected output. The control of the RTU is based on model predictive methods.

  3. Comparison of AEO 2005 natural gas price forecast to NYMEX futures prices

    SciTech Connect

    Bolinger, Mark; Wiser, Ryan

    2004-12-13

    On December 9, the reference case projections from ''Annual Energy Outlook 2005 (AEO 2005)'' were posted on the Energy Information Administration's (EIA) web site. As some of you may be aware, we at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk. As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past four years, forward natural gas contracts (e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past four years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation (presuming that long-term price stability is valued). In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2005. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or, more recently (and briefly), http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past four AEO releases (AEO 2001-AE0 2004), we once again find that the AEO 2005 reference case gas price forecast falls well below

  4. Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX FuturesPrices

    SciTech Connect

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

    On December 12, 2005, the reference case projections from ''Annual Energy Outlook 2006'' (AEO 2006) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past five years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past five years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2006. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past five AEO releases (AEO 2001-AEO

  5. Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX FuturesPrices

    SciTech Connect

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

    On December 5, 2006, the reference case projections from 'Annual Energy Outlook 2007' (AEO 2007) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past six years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past six years at least, levelized cost comparisons of fixed-price renewable generation with variable-price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are 'biased' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2007. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past six AEO releases (AEO 2001-AEO 2006), we

  6. 2007 Wholesale Power Rate Case Final Proposal : Market Price Forecast Study.

    SciTech Connect

    United States. Bonneville Power Administration.

    2006-07-01

    This study presents BPA's market price forecasts for the Final Proposal, which are based on AURORA modeling. AURORA calculates the variable cost of the marginal resource in a competitively priced energy market. In competitive market pricing, the marginal cost of production is equivalent to the market-clearing price. Market-clearing prices are important factors for informing BPA's power rates. AURORA was used as the primary tool for (a) estimating the forward price for the IOU REP Settlement benefits calculation for fiscal years (FY) 2008 and 2009, (b) estimating the uncertainty surrounding DSI payments and IOU REP Settlements benefits, (c) informing the secondary revenue forecast and (d) providing a price input used for the risk analysis. For information about the calculation of the secondary revenues, uncertainty regarding the IOU REP Settlement benefits and DSI payment uncertainty, and the risk run, see Risk Analysis Study WP-07-FS-BPA-04.

  7. A Chronological Reliability Model Incorporating Wind Forecasts to Assess Wind Plant Reserve Allocation: Preprint

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    * NREL/CP-500-32210 A Chronological Reliability Model Incorporating Wind Forecasts to Assess Wind Plant Reserve Allocation Preprint Michael Milligan To be presented at the American Wind Energy Association WindPower 2002 Conference Portland, Oregon June 3 - June 5, 2002 National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401-3393 NREL is a U.S. Department of Energy Laboratory Operated by Midwest Research Institute * Battelle * Bechtel Contract No. DE-AC36-99-GO10337

  8. Integrated rural energy planning

    SciTech Connect

    El Mahgary, Y.; Biswas, A.K.

    1985-01-01

    This book presents papers on integrated community energy systems in developing countries. Topics considered include an integrated rural energy system in Sri Lanka, rural energy systems in Indonesia, integrated rural food-energy systems and technology diffusion in India, bringing energy to the rural sector in the Philippines, the development of a new energy village in China, the Niaga Wolof experimental rural energy center, designing a model rural energy system for Nigeria, the Basaisa village integrated field project, a rural energy project in Tanzania, rural energy development in Columbia, and guidelines for the planning, development and operation of integrated rural energy projects.

  9. Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

    SciTech Connect

    Jacobs, John M.; Rhodes, M.; Brown, C. W.; Hood, Raleigh R.; Leight, A.; Long, Wen; Wood, R.

    2014-11-01

    The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.

  10. Turbulence-driven coronal heating and improvements to empirical forecasting of the solar wind

    SciTech Connect

    Woolsey, Lauren N.; Cranmer, Steven R.

    2014-06-01

    Forecasting models of the solar wind often rely on simple parameterizations of the magnetic field that ignore the effects of the full magnetic field geometry. In this paper, we present the results of two solar wind prediction models that consider the full magnetic field profile and include the effects of Alfvn waves on coronal heating and wind acceleration. The one-dimensional magnetohydrodynamic code ZEPHYR self-consistently finds solar wind solutions without the need for empirical heating functions. Another one-dimensional code, introduced in this paper (The Efficient Modified-Parker-Equation-Solving Tool, TEMPEST), can act as a smaller, stand-alone code for use in forecasting pipelines. TEMPEST is written in Python and will become a publicly available library of functions that is easy to adapt and expand. We discuss important relations between the magnetic field profile and properties of the solar wind that can be used to independently validate prediction models. ZEPHYR provides the foundation and calibration for TEMPEST, and ultimately we will use these models to predict observations and explain space weather created by the bulk solar wind. We are able to reproduce with both models the general anticorrelation seen in comparisons of observed wind speed at 1 AU and the flux tube expansion factor. There is significantly less spread than comparing the results of the two models than between ZEPHYR and a traditional flux tube expansion relation. We suggest that the new code, TEMPEST, will become a valuable tool in the forecasting of space weather.

  11. National forecast for geothermal resource exploration and development with techniques for policy analysis and resource assessment

    SciTech Connect

    Cassel, T.A.V.; Shimamoto, G.T.; Amundsen, C.B.; Blair, P.D.; Finan, W.F.; Smith, M.R.; Edeistein, R.H.

    1982-03-31

    The backgrund, structure and use of modern forecasting methods for estimating the future development of geothermal energy in the United States are documented. The forecasting instrument may be divided into two sequential submodels. The first predicts the timing and quality of future geothermal resource discoveries from an underlying resource base. This resource base represents an expansion of the widely-publicized USGS Circular 790. The second submodel forecasts the rate and extent of utilization of geothermal resource discoveries. It is based on the joint investment behavior of resource developers and potential users as statistically determined from extensive industry interviews. It is concluded that geothermal resource development, especially for electric power development, will play an increasingly significant role in meeting US energy demands over the next 2 decades. Depending on the extent of R and D achievements in related areas of geosciences and technology, expected geothermal power development will reach between 7700 and 17300 Mwe by the year 2000. This represents between 8 and 18% of the expected electric energy demand (GWh) in western and northwestern states.

  12. Evaluation of Forecasted Southeast Pacific Stratocumulus in the NCAR, GFDL and ECMWF Models

    SciTech Connect

    Hannay, C; Williamson, D L; Hack, J J; Kiehl, J T; Olson, J G; Klein, S A; Bretherton, C S; K?hler, M

    2008-01-24

    We examine forecasts of Southeast Pacific stratocumulus at 20S and 85W during the East Pacific Investigation of Climate (EPIC) cruise of October 2001 with the ECMWF model, the Atmospheric Model (AM) from GFDL, the Community Atmosphere Model (CAM) from NCAR, and the CAM with a revised atmospheric boundary layer formulation from the University of Washington (CAM-UW). The forecasts are initialized from ECMWF analyses and each model is run for 3 days to determine the differences with the EPIC field data. Observations during the EPIC cruise show a stable and well-mixed boundary layer under a sharp inversion. The inversion height and the cloud layer have a strong and regular diurnal cycle. A key problem common to the four models is that the forecasted planetary boundary layer (PBL) height is too low when compared to EPIC observations. All the models produce a strong diurnal cycle in the Liquid Water Path (LWP) but there are large differences in the amplitude and the phase compared to the EPIC observations. This, in turn, affects the radiative fluxes at the surface. There is a large spread in the surface energy budget terms amongst the models and large discrepancies with observational estimates. Single Column Model (SCM) experiments with the CAM show that the vertical pressure velocity has a large impact on the PBL height and LWP. Both the amplitude of the vertical pressure velocity field and its vertical structure play a significant role in the collapse or the maintenance of the PBL.

  13. Forecasting the Magnitude of Sustainable Biofeedstock Supplies: the Challenges and the Rewards

    SciTech Connect

    Graham, Robin Lambert

    2007-01-01

    Forecasting the magnitude of sustainable biofeedstock supplies is challenging because of 1) the myriad of potential feedstock types and their management 2) the need to account for the spatial variation of both the supplies and their environmental and economic consequences, and 3) the inherent challenges of optimizing across economic and environmental considerations. Over the last two decades U.S. biomass forecasts have become increasingly complex and sensitive to environmental and economic considerations. More model development and research is needed however, to capture the landscape and regional tradeoffs of differing biofeedstock supplies especially with regards water quality concerns and wildlife/biodiversity. Forecasts need to be done in the context of the direction of change and what the probable land use and attendant environmental and economic outcomes would be if biofeedstocks were not being produced. To evaluate sustainability, process-oriented models need to be coupled or used to inform sector models and more work needs to be done on developing environmental metrics that are useful for evaluating economic and environmental tradeoffs. These challenges are exciting and worthwhile as they will enable the bioenergy industry to capture environmental and social benefits of biofeedstock production and reduce risks.

  14. Why Models Don%3CU%2B2019%3Et Forecast.

    SciTech Connect

    McNamara, Laura A.

    2010-08-01

    The title of this paper, Why Models Don't Forecast, has a deceptively simple answer: models don't forecast because people forecast. Yet this statement has significant implications for computational social modeling and simulation in national security decision making. Specifically, it points to the need for robust approaches to the problem of how people and organizations develop, deploy, and use computational modeling and simulation technologies. In the next twenty or so pages, I argue that the challenge of evaluating computational social modeling and simulation technologies extends far beyond verification and validation, and should include the relationship between a simulation technology and the people and organizations using it. This challenge of evaluation is not just one of usability and usefulness for technologies, but extends to the assessment of how new modeling and simulation technologies shape human and organizational judgment. The robust and systematic evaluation of organizational decision making processes, and the role of computational modeling and simulation technologies therein, is a critical problem for the organizations who promote, fund, develop, and seek to use computational social science tools, methods, and techniques in high-consequence decision making.

  15. Procurement Integrity | Department of Energy

    Energy Saver

    Procurement Integrity Procurement Integrity PDF icon Procurement Integrity More Documents & Publications POLICY FLASH 2016-04 AcqGuide3pt1.doc&0; Chapter 3 - Improper Business...

  16. Integrating Solar PV in Utility System Operations: Analytical Framework and Arizona Case Study

    SciTech Connect

    Wu, Jing; Botterud, Audun; Mills, Andrew; Zhou, Zhi; Hodge, Bri-Mathias; Mike, Heaney

    2015-06-01

    A systematic framework is proposed to estimate the impact on operating costs due to uncertainty and variability in renewable resources. The framework quantifies the integration costs associated with subhourly variability and uncertainty as well as day-ahead forecasting errors in solar PV (photovoltaics) power. A case study illustrates how changes in system operations may affect these costs for a utility in the southwestern United States (Arizona Public Service Company). We conduct an extensive sensitivity analysis under different assumptions about balancing reserves, system flexibility, fuel prices, and forecasting errors. We find that high solar PV penetrations may lead to operational challenges, particularly during low-load and high solar periods. Increased system flexibility is essential for minimizing integration costs and maintaining reliability. In a set of sensitivity cases where such flexibility is provided, in part, by flexible operations of nuclear power plants, the estimated integration costs vary between $1.0 and $4.4/MWh-PV for a PV penetration level of 17%. The integration costs are primarily due to higher needs for hour-ahead balancing reserves to address the increased sub-hourly variability and uncertainty in the PV resource. (C) 2015 Elsevier Ltd. All rights reserved.

  17. Defense Nuclear Material Stewardship Integrated Inventory Information Management System (IIIMS).

    SciTech Connect

    Aas, Christopher A.; Lenhart, James E.; Bray, Olin H.; Witcher, Christina Jenkin

    2004-11-01

    Sandia National Laboratories was tasked with developing the Defense Nuclear Material Stewardship Integrated Inventory Information Management System (IIIMS) with the sponsorship of NA-125.3 and the concurrence of DOE/NNSA field and area offices. The purpose of IIIMS was to modernize nuclear materials management information systems at the enterprise level. Projects over the course of several years attempted to spearhead this modernization. The scope of IIIMS was broken into broad enterprise-oriented materials management and materials forecasting. The IIIMS prototype was developed to allow multiple participating user groups to explore nuclear material requirements and needs in detail. The purpose of material forecasting was to determine nuclear material availability over a 10 to 15 year period in light of the dynamic nature of nuclear materials management. Formal DOE Directives (requirements) were needed to direct IIIMS efforts but were never issued and the project has been halted. When restarted, duplicating or re-engineering the activities from 1999 to 2003 is unnecessary, and in fact future initiatives can build on previous work. IIIMS requirements should be structured to provide high confidence that discrepancies are detected, and classified information is not divulged. Enterprise-wide materials management systems maintained by the military can be used as overall models to base IIIMS implementation concepts upon.

  18. Integrated assessment of dispersed energy resources deployment

    SciTech Connect

    Marnay, Chris; Blanco, Raquel; Hamachi, Kristina S.; Kawaan, Cornelia P.; Osborn, Julie G.; Rubio, F. Javier

    2000-06-01

    The goal of this work is to create an integrated framework for forecasting the adoption of distributed energy resources (DER), both by electricity customers and by the various institutions within the industry itself, and for evaluating the effect of this adoption on the power system, particularly on the overall reliability and quality of electrical service to the end user. This effort and follow on contributions are intended to anticipate and explore possible patterns of DER deployment, thereby guiding technical work on microgrids towards the key technical problems. An early example of this process addressed is the question of possible DER adopting customer disconnection. A deployment scenario in which many customers disconnect from their distribution company (disco) entirely leads to a quite different set of technical problems than a scenario in which customers self generate a significant share or all of their on-site electricity requirements and additionally buy and sell energy and ancillary services (AS) locally and/or into wider markets. The exploratory work in this study suggests that the economics under which customers disconnect entirely are unlikely.

  19. Energy Systems Integration

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Systems Integration Ben Kroposki, PhD, PE Director, Energy Systems Integration National Renewable Energy Laboratory 2 Reducing investment risk and optimizing systems in a rapidly changing energy world * Increasing penetration of variable RE in grid * Increasing ultra high energy efficiency buildings and controllable loads * New data, information, communications and controls * Electrification of transportation and alternative fuels * Integrating energy storage (stationary and mobile) and thermal

  20. Residential Buildings Integration (RBI)

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    | Energy Efficiency and Renewable Energy eere.energy.gov David Lee Program Manager Residential Buildings Integration (RBI) April 22, 2014 Residential Buildings Integration (RBI) Mission/Vision The Residential Buildings Integration (RBI) program's mission: To accelerate energy performance improvements in residential buildings by developing, demonstrating, and deploying a suite of cost-effective technologies, tools, and solutions to achieve peak performance in new and existing homes. RBI Vision,

  1. Wind Energy Integration: Slides

    WindExchange

    information about integrating wind energy into the electricity grid. Wind Energy Integration Photo by Dennis Schroeder, NREL 25907 Wind energy currently contributes significant power to energy portfolios around the world. *U.S. Department of Energy. (August 2015). 2014 Wind Technologies Market Report. Wind Energy Integration In 2014, Denmark led the way with wind power supplying roughly 39% of the country's electricity demand. Ireland, Portugal, and Spain provided more than 20% of their

  2. Distribution Grid Integration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    ... Sandia, DOE Energy Storage Program, GeneSiC Semiconductor, U.S. Army ARDEC: Ultra-High-Voltage Silicon Carbide Thyristors Capabilities, Distribution Grid Integration, Energy, ...

  3. Commercial Buildings Integration

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Buildings Integration Images courtesy CREE, True Manufacturing, A.O. Smith, Bernstein Associates, Cambridge Engineering, Alliance Laundry Systems, NREL 2 Strategic Fit within ...

  4. "Integrated Gasification Combined Cycle"

    Energy Information Administration (EIA) (indexed site)

    Plant",,,"X" " - CCS","X" "Integrated Gasification Combined Cycle" " - Advanced ... of Plant",,,"X" "Advanced Nuclear","X" "Biomass" " - Pulverized Coal",,,"X" " - Fuel ...

  5. Sandia Energy - Grid Integration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    of Sandia's larger portfolio of renewable energy technology programs (Wind, Solar Power, Geothermal, and Energy Systems Analysis). Transmission Grid Integration The goal of...

  6. Integrating Electricity Subsector

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Integrating Electricity Subsector Failure Scenarios into a Risk Assessment Methodology ... Department of Energy (DOE), Office of Electricity Delivery and Energy Reliability (OE) ...

  7. integrated-transportation-models

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    support a wider application of integrated transportation models, especially focusing on travel demand and network ... irrevocable worldwide license in said article to ...

  8. CLASIC DATA INTEGRATION

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Oklahoma Lightning Mapping Array, NLDN NOAA Profiler Network Kessler Farm Field Laboratory ASOS, AWOS, AWSS (FAANWSDOD) ARM & Oklahoma Dataset Integration: Examples Oklahoma ...

  9. NREL: Energy Systems Integration - Events

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    archive. Printable Version Energy Systems Integration Home Capabilities Research & Development Facilities Working with Us Publications News Events Energy Systems Integration...

  10. NREL: Transmission Grid Integration - Publications

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Publications Want updates about future transmission grid integration webinars and ... and Transmission Study Flexible Energy Scheduling Tool for Integration of ...

  11. PEV Integration with Renewables (Presentation)

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    solar inverter technology for vehicle export power integration 60% 6 Approach - Electric Vehicle Grid Integration Strategy * Objectives: - Infrastructure planning supporting ...

  12. Systems Integration (Fact Sheet)

    SciTech Connect

    Not Available

    2011-10-01

    The Systems Integration (SI) subprogram works closely with industry, universities, and the national laboratories to overcome technical barriers to the large-scale deployment of solar technologies. To support these goals, the subprogram invests primarily in four areas: grid integration, technology validation, solar resource assessment, and balance of system development.

  13. Systems Integration (Fact Sheet)

    SciTech Connect

    DOE Solar Energy Technologies Program

    2011-10-13

    The Systems Integration (SI) subprogram works closely with industry, universities, and the national laboratories to overcome technical barriers to the large-scale deployment of solar technologies. To support these goals, the subprogram invests primarily in four areas: grid integration, technology validation, solar resource assessment, and balance of system development.

  14. Integrating Module - NEMS Documentation

    Reports and Publications

    2014-01-01

    Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

  15. Use of Data Denial Experiments to Evaluate ESA Forecast Sensitivity Patterns

    SciTech Connect

    Zack, J; Natenberg, E J; Knowe, G V; Manobianco, J; Waight, K; Hanley, D; Kamath, C

    2011-09-13

    The overall goal of this multi-phased research project known as WindSENSE is to develop an observation system deployment strategy that would improve wind power generation forecasts. The objective of the deployment strategy is to produce the maximum benefit for 1- to 6-hour ahead forecasts of wind speed at hub-height ({approx}80 m). In this phase of the project the focus is on the Mid-Columbia Basin region which encompasses the Bonneville Power Administration (BPA) wind generation area shown in Figure 1 that includes Klondike, Stateline, and Hopkins Ridge wind plants. The Ensemble Sensitivity Analysis (ESA) approach uses data generated by a set (ensemble) of perturbed numerical weather prediction (NWP) simulations for a sample time period to statistically diagnose the sensitivity of a specified forecast variable (metric) for a target location to parameters at other locations and prior times referred to as the initial condition (IC) or state variables. The ESA approach was tested on the large-scale atmospheric prediction problem by Ancell and Hakim 2007 and Torn and Hakim 2008. ESA was adapted and applied at the mesoscale by Zack et al. (2010a, b, and c) to the Tehachapi Pass, CA (warm and cools seasons) and Mid-Colombia Basin (warm season only) wind generation regions. In order to apply the ESA approach at the resolution needed at the mesoscale, Zack et al. (2010a, b, and c) developed the Multiple Observation Optimization Algorithm (MOOA). MOOA uses a multivariate regression on a few select IC parameters at one location to determine the incremental improvement of measuring multiple variables (representative of the IC parameters) at various locations. MOOA also determines how much information from each IC parameter contributes to the change in the metric variable at the target location. The Zack et al. studies (2010a, b, and c), demonstrated that forecast sensitivity can be characterized by well-defined, localized patterns for a number of IC variables such as 80-m

  16. Climatic Forecasting of Net Infiltration at Yucca Montain Using Analogue Meteororological Data

    SciTech Connect

    B. Faybishenko

    2006-09-11

    At Yucca Mountain, Nevada, future changes in climatic conditions will most likely alter net infiltration, or the drainage below the bottom of the evapotranspiration zone within the soil profile or flow across the interface between soil and the densely welded part of the Tiva Canyon Tuff. The objectives of this paper are to: (a) develop a semi-empirical model and forecast average net infiltration rates, using the limited meteorological data from analogue meteorological stations, for interglacial (present day), and future monsoon, glacial transition, and glacial climates over the Yucca Mountain region, and (b) corroborate the computed net-infiltration rates by comparing them with the empirically and numerically determined groundwater recharge and percolation rates through the unsaturated zone from published data. In this paper, the author presents an approach for calculations of net infiltration, aridity, and precipitation-effectiveness indices, using a modified Budyko's water-balance model, with reference-surface potential evapotranspiration determined from the radiation-based Penman (1948) formula. Results of calculations show that net infiltration rates are expected to generally increase from the present-day climate to monsoon climate, to glacial transition climate, and then to the glacial climate. The forecasting results indicate the overlap between the ranges of net infiltration for different climates. For example, the mean glacial net-infiltration rate corresponds to the upper-bound glacial transition net infiltration, and the lower-bound glacial net infiltration corresponds to the glacial transition mean net infiltration. Forecasting of net infiltration for different climate states is subject to numerous uncertainties-associated with selecting climate analogue sites, using relatively short analogue meteorological records, neglecting the effects of vegetation and surface runoff and runon on a local scale, as well as possible anthropogenic climate changes.

  17. Validation of a 20-year forecast of US childhood lead poisoning: Updated prospects for 2010

    SciTech Connect

    Jacobs, David E. . E-mail: dejacobs@starpower.net; Nevin, Rick

    2006-11-15

    We forecast childhood lead poisoning and residential lead paint hazard prevalence for 1990-2010, based on a previously unvalidated model that combines national blood lead data with three different housing data sets. The housing data sets, which describe trends in housing demolition, rehabilitation, window replacement, and lead paint, are the American Housing Survey, the Residential Energy Consumption Survey, and the National Lead Paint Survey. Blood lead data are principally from the National Health and Nutrition Examination Survey. New data now make it possible to validate the midpoint of the forecast time period. For the year 2000, the model predicted 23.3 million pre-1960 housing units with lead paint hazards, compared to an empirical HUD estimate of 20.6 million units. Further, the model predicted 498,000 children with elevated blood lead levels (EBL) in 2000, compared to a CDC empirical estimate of 434,000. The model predictions were well within 95% confidence intervals of empirical estimates for both residential lead paint hazard and blood lead outcome measures. The model shows that window replacement explains a large part of the dramatic reduction in lead poisoning that occurred from 1990 to 2000. Here, the construction of the model is described and updated through 2010 using new data. Further declines in childhood lead poisoning are achievable, but the goal of eliminating children's blood lead levels {>=}10 {mu}g/dL by 2010 is unlikely to be achieved without additional action. A window replacement policy will yield multiple benefits of lead poisoning prevention, increased home energy efficiency, decreased power plant emissions, improved housing affordability, and other previously unrecognized benefits. Finally, combining housing and health data could be applied to forecasting other housing-related diseases and injuries.

  18. U.S. oil production forecast update reflects lower rig count

    Energy Information Administration (EIA) (indexed site)

    U.S. oil production forecast update reflects lower rig count Lower oil prices and fewer rigs drilling for crude oil are expected to slow U.S. oil production growth this year and in 2016. U.S. crude oil production is still expected to average 9.2 million barrels per day this year. That's up half a million barrels per day from last year and the highest output level in more than four decades. A substantial part of the year-over-year increase reflects rapid production growth throughout 2014.

  19. Energy Savings Forecast of Solid-State Lighting in General Illumination Applications

    SciTech Connect

    none,

    2014-08-29

    With declining production costs and increasing technical capabilities, LED adoption has recently gained momentum in general illumination applications. This is a positive development for our energy infrastructure, as LEDs use significantly less electricity per lumen produced than many traditional lighting technologies. The U.S. Department of Energy’s Energy Savings Forecast of Solid-State Lighting in General Illumination Applications examines the expected market penetration and resulting energy savings of light-emitting diode, or LED, lamps and luminaires from today through 2030.

  20. RACORO Forecasting

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    7a. Space Heating by Census Region and Climate Zone, Million U.S. Households, 1993 Space Heating Characteristics RSE Column Factor: Total Census Region Climate Zone RSE Row Factors Northeast Midwest South West Fewer than 2,000 CDD and -- More than 2,000 CDD and Few- er than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Few- er than 4,000 HDD 0.5 0.9 1.1 0.8 0.8 1.6 1.3 1.2 1.2 1.1 Total ................................................. 96.6 19.5 23.3 33.5 20.4 8.7 26.5